{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import torch\n",
    "from torch.autograd import Variable\n",
    "import torch.nn as nn\n",
    "import torch.nn.init as init\n",
    "import torch.nn.functional as F\n",
    "import torch.optim as optim\n",
    "import numpy as np\n",
    "from six.moves import cPickle as pickle\n",
    "from six.moves import range\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train set (750, 1, 64, 64) (750, 6)\n"
     ]
    }
   ],
   "source": [
    "pickle_file = 'small_321_train.pickle'\n",
    "\n",
    "with open(pickle_file, 'rb') as f:\n",
    "    save = pickle.load(f)\n",
    "    train_dataset = save['small_data']\n",
    "    train_labels = save['small_target']\n",
    "    del save  # hint to help gc free up memory\n",
    "    print('train set', train_dataset.shape, train_labels.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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q15K9yxljafxy7nvWcjpjR3Os2E75UhvXvkEtJ7pd7dJUBqP+jKJ0UfmeVWS/\ni8gLL7ywTVO5kL1pyd5G9cmpfxTRyrHX0RhK9zcak/Setf4547nWSz1W0fmilqlavdT+RGPrqIyp\nHlP70rml5lfLgJazcCLo6X3o/Y3mT/Tc9TjtY8iapvek93FI6BITilOPaf41WkKE5paz0SeVWRuV\nY8Hq26l9O3mh/mMpQpV7/plIuE6EM6cvc9436J5o/5FlzLH2Otfchyh8QgghhBBCCCGEEFZGPviE\nEEIIIYQQQgghrIxztXRR5CiVOpFFShmt3E82J5Kg04rdCkk/9T5UNkmyPc2DSs/7sXQOkqZpfh27\nh6YpSgPZHUY2Lk2rbPLq1avDtFq6VIpLURTI3qPos9F99Px6r3r+fq+ONJ1k1VpeJOM9JKi+kgWL\n5KSjspuN7ORAfQNZqmatWX07RVuZtWI5q+wvRQzbZelas+cjyCLr2KjIXkPbe/pORNqave+Lgkr6\nHZvRTJRFp02T/ciBouwoZP9ZirDpWKjInqxj35LlejePFAFpxtLl9Ld0/0t2mqrbxyG9vtqVtT3o\nsWRp6XlzrOMUVZXa4KFavdQ2ThHQKPoRRW0ZlYUTbY7qNFmbyAZB/T2NIXrfvR6R5cmJdnfz5s1t\nWi39Cs2zHKsNLYMw6lcUsmKTZVLzSPWb9tfza5ulZSn689C8q41LI9xqfdB70rLW6HNkq7vo6PIR\nhJa/3r+2a7UYjsqZ0GfuLJNBbZPGUMcuPZqzOuOKY0EcLZNx0vVprKQxb1QGWkaObZjsrNqmdH+a\nO1BZ67HU5/c8U33QPNI8g/r22WUKovAJIYQQQgghhBBCWBn54BNCCCGEEEIIIYSwMs7V0uXYFxSS\nlS1J80lyRZEoVBalFiWVPj7yyCPD9MMPP7xNO1GkRhIsknTTqvEkv9aIERSNQ1HJpxPBRPPej9Xy\n0nJROSWVqeJEO9O0SlQ1X7pdpagq4evnUdkdSeCXbAW76UO1dDn2BScSkDKyb1F5OlJ/klQr+0TG\nGlkPHEsXtdNZG5cTScs5drSv4tjqnDpAstSRfbKKrTOj/bWfoOsv3X/V7WWwjx3sbuLIdp3oVspS\n1AuF7K6z0TXp/GRHIwt434ck1ySFVksyWV5IOk1112kno/3pHE40ELJ0qaScrDBajhSFlGy8oyhd\neg7H0kT2BCdazEXkxo0b2zTZfHTuQWUxsnSR1UH7S31uFKHKWRqAlh2gJQboefV9lqzSu+fQctHy\nonqseV+907nnAAAgAElEQVSKqOTmvd+rcw7HqjprUyQbl96rtrfRvEOfl/Z3ehxFr9L3BC13bcuH\nBPVphDM3Hc2pnDGWLNLOux8tOUJzKD2PPruRJVfTNLekvCsU6cpZ5oTG/9HcgeZzNGZpn+hEuHWs\nVvScqG32tBOBmyJ2z0Z5Iw5zBhxCCCGEEEIIIYQQkHzwCSGEEEIIIYQQQlgZ52rpIqmkI88kaWmX\nSzmSfj2HylZVfnXp0qVt+qGHHtqmr1y5sk0/+eST27RGoFKp5GzUlFF+VdapckuNYvD8889v0ySp\nJksIWXGcKA0dksOrpUtlaiTJc2SRuo9el/JAcr6eH5JEKhSNgmxcjtT3IqL3Pxt9acY2Qu3UsTY5\n0bAc65Zj9erblyTUJ6Udexnd66wcnfrKEU7fNBv1yLF00T6j/R2LqWMrVM4qQtx549hdaB/tD5ds\nIyTXViiippMXkriT7XpJsq5/J/sinW8ULfOk7XSe06ZJgk/1WMuUInBS5FOaC8zaxPo4p3YlTeu+\nOnehPlQ51Ah6Oi/TeyNbkpYXtaVRuyJLl85xFGeu61iXHFvBjMWALLmEM1+lsYrGmKWoeDTnXIqk\ndlK+FCpHioalz8xp46P80nN05rFkn7/o0Luf4szXR9ZhKk+qF2RrpHbvRM2j8UyhSNOjczvWce1v\ntE3R8hi0dIoTYWtpSQiyoTrvgLTsC81vFeq3dP9R26M5rUL1h+yks++bUfiEEEIIIYQQQgghrIx8\n8AkhhBBCCCGEEEJYGXfN0uVE7KBV1lUO1W1UKmlUmZOuVE9oZCeNNPX6179+m37jG9+4Tb/uda/b\npq9evbpNU0QaZRTxxLGBaASu+++//+POUeVJqmdXdifZXLdsaZQytXFpHvWaKvfT62geFZJi0kr3\nKuFT651Kr7t0VqXWFA1Cz01WFa3LJMu96JDccNbSNYqm50i+SaZI0T4cq5cTKWTJmuXYwpzrkJWC\n9idmpOQkC3bk3WTj0j5gH0uX2jBH+1P7JpntoUbgcnCk6QRFWOnlpeXmSPediJpkISZozCc7Ws8z\nWVWca5Lliura7D50Hz1NEcZI6k51gCwvZDOgfpP6XK0TfezWMVzHba1rTkRDZTai0UVB75ns+Jom\nS9cIKhM9Tp+z9qNOBEPq+ylNfc8oaizNFShf1AfoOKF50fmlzvl0WQWd11NEWqWXt/Oe4ozzToRI\nfWZajtrGnPP0fZwlLMiqeqi2SgfHsqjQ/LYfS3Nex4pP1iKal1FeaM5FdaDnh8YvZyxTtL7q+xON\nYfQ+T2OPllk/J9VpbfcUFVrPrf0BzZOp36J+m/rlkaWL5ge6z51oj+udJYcQQgghhBBCCCHco+SD\nTwghhBBCCCGEEMLKOFdLF0U5opW8R5KuqtulZF0ORTJnlW6RLEsjbb3hDW/Ypt/ylrds029729u2\nabWJqWRM80XSvtE+lF+VrTqrh6t0+NatW9s0yeBIikiSNb3vkaVLpXSOLUhtVpom6Ztj8dM8vulN\nb9qmVXJ4/fr12oUsXQpJ/DSa26HiRGtybDMjGStJHXVfihBB9dKxDDj7L51nH0sXpRVHeq84z6DX\nUz0fWUicCBMKRRiZtQQupSmiA12T5NBrwKkXylLEn9lzO5F1nMgjdCz195SHPoZRu6N7pjFU0zS2\n67jpRONasoNR/VYcSw89G7KNUpQfpz/tabKzONahtVkvnUiMs/a2DvVjznIIVOZk6de67tif9Px6\nT31+S/VC579OxB2dA2t+dfkAiqw7a+nq+XTGZCdCoROVUO9pVI67aZqbj/LjRFsja4lehyLYXnRm\nx01iZOmiJR32sTM7lh9Kax6dJQZG19Sxj8YvxwJOczuK1ky281F+KQKX9gf6Tkrti65Jz4MiV9J9\njPpcxz7n9LfKrBV6XaNvCCGEEEIIIYQQQsgHnxBCCCGEEEIIIYS1ca6WLpIVklzJkeaPZHMkbyPZ\nqMqiHnvssW360z/907dptX2R7FxtQTdv3tym1V5148aNjzuPytFI9qXyNbKK6HX0+iT7JkkxReIZ\nnceJaOBA+dJz6naKHKT7kDyvH6vHqZxR7WUU4UzRa1J0tosO2XwUkiUvSflJ2upE5iIZJknjdR+1\nic1awHqenX0dS5cTvcGxOzgWu1FEA7oOWTyp7ZA9ZNaatsRZybGJQ5KpO5YqYml/53z0bGmcnbV0\nUZQMajOjccaxAdOYoXYWHQd0zJ21dC3ZEMmO6ETwc/o7SlM001E0LsrPPn0WcahRuqi/pzKnsh31\nvWTFOm2dq+KoiRTdSo/VOkLWwN5+yOpA9VuhObDau65cuTJMq72L2jItDdDz49gUnXGYjtX71ryQ\ndUvfGZbmNzSPozpAkRDp/eiQcJ6dM/6N2hg9c+fdRdFnTs9Fr0+2K1o2Qen3qvki+yRFx6PoWgrZ\nlfU+6L2cxvxe3tpnaX71HVojbes1te1QlK6liMNVt7/na7nrkiojy5hj+aZ65dh4HaLwCSGEEEII\nIYQQQlgZ+eATQgghhBBCCCGEsDLO1dJFUkrHQjITLUjlT7TaOUUrUEvXk08+uU2rfOzDH/7wNq32\nn+eee26bfv/7379NP/vss8N0l829+c1vHuaRrFUq61OuXr26TWskKpKd6XZHJqzl1NMkQ6TVxkmm\nruWo+4yuuXt+ivJG8sd+XX2OKo/VMtLtdJ1R1LhDg9qU0zaXZIWOlYPsT2RlIPmzPi99vrNRukYR\nxmaOOyntWK0UkpyS5L+fk9qg7qvlrvvfCRk3yWVHaUdqrXmftRuqheGiMxvZyIkO0tuS88xJZk3X\ncaIFKVSnl2xaZP3QPljHDIrwQdYP3U5jG6VnbOpOVEKK2qPSce3vSF5OaScaYYeeI419ur9TNw8J\nGnvI0kWRXEd9I9lwnOiIzhxO67pGt9IoN3rsiy++uE3r/Y2WHtC/K3r/tA9FDtI8qo1L7Ry6D80d\n6T1kFJmTbCtqeaGouY49k2yxmge1kGj5jawl9L5DcwWybjm2tovO7LxToXbVIXsSzUPI9k/vpBRZ\nWduD1mmtF4ru0+spWTnVCqXvu8590Ds3WZdmreEdKgu1odLcTq+j5UVzFLJ06Xbtw+h9ve/v2G/J\nhknlNTs3jMInhBBCCCGEEEIIYWXkg08IIYQQQgghhBDCyjhXS5dCdoOzwJEvalploCplU1mWystU\nOv38889v00899dQ2/d73vne4/dq1a9t0jyigElqNBqZSVZKQqgRMIxTofdAq4HrsjI1L86PbSMqv\nZafyZo0qppYusu6QdJLulSIQ9eetslm9PlkCqM6SlO+QoHsj+bhCMsT+3KkuEEtRv07aX88/Yzvb\npde1s44+tXuepehDJ7FkiyLpp6ZJcutEfHHS1DYoPYqCQbJVkmM7kWAOCbLgKWQZ1Gcxsic45ePU\nS2c8pzZ42ghbFHGI0mphcfZ3oqbQPVGZ9e1kmXAiF5KdVfchexFZw0bWrV16O3RsIyTTXxtk1SE7\nHlnERzjWG5rDURQ6rd9qidA5FFkiKGLpaHzQbWQJ0TKiMUPTmi9Kkw2TLHEj+69jQ6U5MtkXqY1T\nO1G7lu6j9Uf36cdS2VE/4cyXZm0jFwXHrkUsLSfi2JOcZ+7Mdel9xIlCN7Lt6nG6DIhaunQfWr6A\n7MSad+17NE1zYD3nqP1Q/SbLtRNJ1rGR03iu/aamR+PvUr+ze32nDc6+kxxmSw4hhBBCCCGEEEII\nSD74hBBCCCGEEEIIIayMc7V0kcXGgaSHfbsjc1XZm8qv1FKl8lCKpkNRul544YVtWiN2qe1LbUwq\nzxtt07yovUultSqTU7mdSvU0j1pOJOPWMiNJXs8nWZ40TXJSvQ+NAKH7qBRXz0PWKb2u5lfvqZ9H\n6wPZ5Eh+SXaDQ7WQaFk50XSc7SPIyrBkT9q9jmM5cmxMS1D0A4XkqQRZ3Og+qAyWoiGMrFK726n9\nkuWK7AEju+dJ+5D0vued6pTWH4piQBaSOxF57Dxw+iPahyJpnLTtpOvvg9ZXheo0WQx72rEUOu2F\nrB+OFZrSS1H5qL5ShCxK07FkJ3FsdUtlRjJy6ttJsq6cVR07b5zn4li6Rs+I6h9ZDWjepvMcikLn\nRJ1yxvle75zoZTT/JEsI3QfN66n/oEh4o8ictIwA2bjI7kn9tuZLy4baCdWrboXRvOs1qRz1OtT3\nHGqUrqV3xpNY6g9pbuksO+Bsp7FKn6O2X6rro6Uy9L1S3331HVOvqe+7jqVcy1fbiUbSIpun5pf6\nkBF6DrWF0bl1O81LKCoz9Tf0PrlkpXcsz9R/zM5po/AJIYQQQgghhBBCWBn54BNCCCGEEEIIIYSw\nMs7V0uVYQmj1akXlUKNzkk2CZNwqNSM7AuWXoAgYKhPrkjyVhWnEMJXbaZpWSte0rriuq/l/6EMf\n2qbVgqaQjUsla307RT8gaSPJmzXvmkdafV3LwJFujuoBSaYpcoLWO0cGeEg4Ea30/k8bjYxsSxTt\nhaTNJHnVeqHtV7fP2Cbo79S+SQpN1hqSZDo2NbJs9TTZsmYjZzkRjbSfoAgxlKbICEuQ3P5ORoC8\nG1C/SjYFrWtOWz6LfO2zP0UXIntV305jD1kTlyxibnqmju7Snwf1AU7ELsfqRZLx2QiIo/smOTzZ\nQ+h8zvUvOs44QM+O6kCvy1SG2nfSnET3oUgyOp+jKHRL1sSqsc3IiQynaRrXdIyh+6B7IuubzjU1\nD32eTJYQinpFEX/IEqLo/jrvdfpWvW6/DyeSLUUAU6j+HirOe+VMBGNnvkHtm/rP2fdWsmHq+ZeW\n4aAolrT0h9qitL6q7UvRcqK2SdHp9Fq9PyFLI9nOKO96Hs0XtWV6BtquyGLXy9Kpd87SNLrP7Dwu\nCp8QQgghhBBCCCGElZEPPiGEEEIIIYQQQggr41wtXY70kaTZKs2akeyTLItk5BTZiWxkJMdSSHbb\n5WBkdSCbC0lrSQ7mHEvRUSgPvSzpeZGEUq+vz1TlgSqpVZwoIJSf0fMjqwzJ4emeyBp2SKjccdaa\nt9SWqb1QJCqSe2rbIImsI6UnS6Q+9y4h1fskOSntQ3WUIuicVYS3UeRCZzV/ikRANlfaTlFAyAqj\neRtFY3DKkcruUKPmKU6fQuWs9699eS/zaUnwpNVg9pyOjaqnacya7Y+dqBdOZC6Hfn7KF9Vvp+8h\nezdFOyHLmGM361D0ELo/Kt9DjaBH5UN9/GyfvHQdJ5KMWg00Qo8TYYaiPimjqFdaz3RuR1G6dPzQ\n6+tyCxRRSJdB0PvQsqF6r3nrEXR1m5Y72eT0OjRf1vsj6w7ZWZf6wd3zjK7jWA/1Pqj+HhLO2Eb9\nF9HLiOzU1Eac6FaUJvsY2XyIUR7oOIpkp5armzdvbtNqqdJ6rFBdp3nk6D2frKT0/kjjo2NZ1L6E\nIvGRPW6pPVKEQmr3ZOOanX8c5ttpCCGEEEIIIYQQQkDu2qLNtLiuo5IZfZEjBRB9vdNfDvQXAvpy\nT4vtjRZ9q/r1Xwuqbv/6qV8H+68O9EXSUTE4v5jRryqkZqJfqkYLV5HaSp81La5FvzTo11pSeZEi\nhH59HamfHKWW8ysBfa09JGhRYfqCTG129CycX8dnFzukekm/TtJ2rV9aT0e/5NBie3Ru+pXE+RXf\nUa/QLwa9LKms6Vci+lVJcZ4l1Q1qV6Oycdqg8yvkGhQ+s+oHZ//RPs5xzq+gs/l1FBCjZ01txGlH\nzgLHmqZfbmcXCD+tksUpo1n1jHOepbGA+vBDVezMQnWNfq1XZuoUlTONm7SwKC0ySr9UkxpFGY1z\nNKdVJTEpfHRM0rm5BiK5evXqNq2qJb1vR/k7UvjQArQ0VpKLgBbVpXpCKllN6z56ryNVxazScUbZ\ndwg4i+tT/SZ1Rd+uz1Drt1MvnGuSkpocIOQ4GPUbNC/Veq/tV5U8L7744jat77jkynDqtx5LCt9e\nZpRfqt8UDIjqupavM2en9yZlpKamuTY5cJx3IocofEIIIYQQQgghhBBWRj74hBBCCCGEEEIIIayM\nu2bpUkgWRQs0KV12RQsTalplZJ/5mZ+5Tb/1rW/dpp944oltWqVxJO9SWdnzzz+/TT/99NPbtErJ\nrly5sk2/8MILVVX11FNPbbe94Q1v2KZVwqplRwvDkhxO91dpmJ6fpHqa35FclRa20md648aNbfoD\nH/jANq3yXpLCatnpPrQAmEJWtn4sySMV3U72H1pY+JCgfFObJYsQSVRH20ja6ixkR7JUktiTVWNJ\nhu9ImylfznVmrV7EqB+g40heTgvDzi5Y68iaZxY3p/tw7CxkNTsknOdP9ZTqbN/fWXBS2cfSRdud\nPma0AKv277QoqbO4OlmLnfkK2SaWFi127BOz1rzZc+6TXrrOvcJsuyNrljIKdqDzELJs0Djs2Iz2\nCTwxs2izprUNjhbrr7rdBqLWLV2SQa1pNGfX6yoja47mhebdTl9Gz4PmPbQwrBNQpadng4mQ5dlZ\n1PaiQ3NaJ2jGki2K5pNUVnQ+fYb6LqV1/dKlS9s0LbRO82daDL2jdVHfZfUdUN/frl+/Ptxf6wvd\nK1m6dCmUpTmiWrSoPeo19dzarmmBe7JR6Xbq22g5ln4sLf3hLFtC/QS9txJR+IQQQgghhBBCCCGs\njHzwCSGEEEIIIYQQQlgZ52rpcmSQJE1TuZ1KoEYRO0jWSKvsO/uTlFKlpWqReuyxx7ZplcSprK2j\nsjO1d+k1Vcqn+VVpmsrLrl27tk2r1MyRqJIUVMu9y80cCdysrYOuObvqPlnZliR2jlWF9qdjLzpa\np517oDa7ZGsYtd2Tzq3M2hcc2S3ZmHp/QvuS5JnslmTjIkuVY2Vbgp4F2VbIsjgb4YP6ato+Ewno\nXsSJNEb9MI25o3q0j13LiVDk2O6cPmFk6SJblhPJbR+r32ltTCTXpjnHbHQ8mjuRDc4py76/Y/c4\nVPvkLLN1TVmyMtK8SdPUv9L8y7GUzY6hS7YotWFomqyXFIWWrFAUMVMha8toGQQnMinNBcgO5kSa\ndOyR9Cx7Gej5qF+lcnfs3YeE1guaYziRGJVeRhRRS58/WRb1WLJVOpG5qE5rGxuNDzRXo8hjo0h2\nVWzF0vtwlnug9qj0vNHYpNB7vmOfo4jd9IxPa59XnEhfToQvhyh8QgghhBBCCCGEEFZGPviEEEII\nIYQQQgghrIwLEaXL2Z9Wsh5BkjVnf5Jt0nk0j7qaOkXYGqESsWeffXab1lXQSUKq11RpnMrtVIZH\nq4CTTYzksl3iRhJThaSqTlQTku46x1Ieeprk0MrIxlbFdrHZOn5RmL2Hs7hPsm86ES2cFez3iXLT\n8zMb4cY596zdwTn/knTXkfE6aZJJOxY7OudSXSKZ72wfcKjMWq0ca8BZWG5mo0I5faxjcVgqj33a\nmkL9DUXDnBmH7rTlyWmDZEXReYfaA/o+TrSiJZvmWnBsTrPjQD/WmVs5fTbly7ETk9WK7B89rfVG\n65PaQ/Qcul33p7pIEfeW7Fq7+4wsMmRhIvuklovmUe+P5tTUBqncqe0tRRWl9wctd3ruhxqla3ap\nBSdKat+H7LZO9FhF66XWRbJx0RjjjEO9fum9aXRmzWOPIF11+5Ik+l6pdX2fiH/OPK7n2Vm6RfOi\nS65oOapd6/Lly9v0ww8/vE2r1YveVah/Gs11nPm4Y+lSYukKIYQQQgghhBBCuMfJB58QQgghhBBC\nCCGElXGuli6VuJHsy5GA64rZKkkcnZukd4pKwDSPKtdSKZtu17yrHOwNb3jDNq3SsJH89b777hue\nT61Y169f36ZV+nnz5s1tWmWAmkfdR9HrErTi+iiSBEntHTk+Wbec6GFkIdDnuhSVxpHSOdG7luyG\nF5V9LDGOrL/j1BHaTul9LErUx4zy7kgv97FqUP1yto8sbmSJvQjM3CvZ90ZRSnbRenLRysDFqVOz\n0aL6Oc/KbnOnLUoj2TfZbWel/E7ELJ1zOFFIiN6HkA2ArMKzddex1VF/uhR1kKIoKWuIXOkwGwnS\nscONIIsPRVobWfFOSlM9pvOQTazvQ5G59BxkC9O568svvzxM67yf2qZjMx21fcdCrND8z7FV0nMl\nexdZjXqa6hRFjKI5De1zqDhWfycKW99OljctN3p30QhR+g5GaX2vo8hcCvXlvV1R29U86vsu2b7U\nIqVpwrG5KqP244xfWi4adUvtXWrp0rTuo8+A+nDqc0f2VyeCHs3jyBI4vUzO1N4hhBBCCCGEEEII\n4cKTDz4hhBBCCCGEEEIIK+NcLV0q+5qVMdMK8iMZJsmfnEhEZPdQiZZeS21cuo/mV61ZIzmdSvxU\nVqdSOpWLkdxQJa9kR1O5m0oFFVo1XY/taafcHch+RSuxEzPRXJRZ2wxFljnUiAazOBasUZnOWk9I\nwulIO50oP0vHzubXgeyIZxXtbdQnUjtWifAoYsnudtrHsbzM2l9GUB/gRPk7VGuJltusvYv6o5Gl\ny3kms+3Bsd2R9XCpHjnHUXrmOrvX2qdO9WMpKqFjF3Ms8FQHqL9zbJOjbbNWPqpjh9o2yZJDad2f\n2vWojmi9UDuTpsmuRRGzNE3PfzZyVN9/tHTB7vn0OIrSRfeqc10dewiKpkNtY4QTTYjaBtlZNF9O\nWS89A7qm1h+9Z70PJ0LiIeFEWHUic43Kn6K0URRkraNqG1LLkabVZkQWMJ3H0Xur1pde77XtaFvQ\nOqJ1UctI86Lvj5rWfJFNUNuy02+O6rfzrqf5IkuX7kP3p/VBnyXZ7UbfDshKSn2G0wZj6QohhBBC\nCCGEEEK4x8kHnxBCCCGEEEIIIYSVca6WLsWRRzrHLkmOSaI9K90m25UjgyTZXJeJqQROr6myN430\nde3ateG51QJGli6Vsmneneg3S5YuZTYyBVlOSMrmRGNQRtsp7ySxIyk9yZvvRZbkvyQdp0gQTvQY\nJ+oFpUnGO1pZ37GCEXTflHbq8ZKNadReq26Xnmq/5mx35Kx6LadvHd23Y3ub5VCl6cpsJLeZcqTy\nOasoYU5/q5ZBrUej7bMWRGoPNBcgZiOMjLY79qulvmn32H36JOqflsZisuNTfXTqwCHhRONyxh6l\nlz9Zb/SZqE2C7FoU3UrTNOdbslhU3T7mjqLpOOXiRBujyEFaNmTR0jKgiLsj6wX1DVReZFslawvZ\n7Rwbl9MPLeXFscDf6QiMdwqaK81GEBz1t84yDjTnUluWvtfpu5lu1/SlS5e2aa1rumwIjQOjCHr6\nbDWPWtd1Lkh5pKVCKOKf5kvbo/ZJI+vl7Hir90HzCWfuoPeh2/VZajk5tvoO1Ueqv3st93DqI0MI\nIYQQQgghhBDChSQffEIIIYQQQgghhBBWxl2zdCkkO1eZFq0y37er1FFxol5QNDAnigVJvUgKrbKv\nfk6yUuh9qnxOV3O/fv36Nk2r/KtUlKJLObaJUZk5UjPHluNEQSGJnbIkk9Z9SAborJqu9Yrse4fE\nrKT+bsh86ZrUZ1DkAkqP2v6MRfA0zEatISvjqG9zLF2OtHXW6uVYZ5YsXRQ9Q6FnNyv7PST2ubfR\nPmdVJlSPtb46+5BlcJQmS+HScbv7a10n28Y+tsJRv0I2DbJ7kPVDz0N2FqfOUAQRpT8/mvMQjk3u\nUC1dxFnYIMnyTPWFbPxqk1Drh9oRtPy1zyarlW6nZQ1GUJ3Tc2hdVyuW5l2tJQpFF6Ky0WuN3iGc\nKK2OzZbmiBR5TPPrRBIbWcmo76V3mTVYnhXn/mlepM9o9Nzp2ZKlT/tJigqlUaQ0TfYuzQMtGzIa\nc6m9ap3WPOr7puaL5oI0nmpd1zao7fqFF17YprU99P5G8+5Y85wolo61mb4XOJFnl/rE2WtSP+QQ\nhU8IIYQQQgghhBDCysgHnxBCCCGEEEIIIYSVca6WLpIPkiSOIiGR5WYEWQNIAqb7U4QCzaNKW9Ve\npWm6VpfEqaxQZbZaXhQtS/P79NNPb9Mq9XJWMCc554zU+qxk2Y5thSIKkMRuJHGn4xw5NkXsUqni\nITFr7SALwFLkCCo3B2rLTmQuJ5rKSDo9G/nGYZ9V9uk8I/knRSXQNPUrTnQjOg8dSxLVUTvV56v7\nknWX+oMZu8Eh4FginAg5vcxnI5k4VgaSlDtWXbIJjtJOfSWpue5DbcCxBDh1atSv7BPRybFIz0bJ\npGc8si47feJSJNVdZqXpF5HZSIxL5ULnc6xQaglSy4RaQtQyQRb12UiXM9B9qC1L51M3btzYprUt\na/1Wm4men5Y40O0disDlPAOKoqX3RBYW3U7RiihqbO+3KJob9ZXOe9Bpn+/dhvoxGsO0LlDktV7+\nNP+lOqLXpIhdmlZLlT47hZ4LRaYanUfrpV5T64hGBrty5cri/loGWqZav7UNasQ9bQ/aBjSfI2hO\nTfZJer56T7PRpZci91GdceZaTv11iMInhBBCCCGEEEIIYWXkg08IIYQQQgghhBDCyrgQli6Sozsr\nyHeZmsqcSJqnEi2VeqnU7NFHH92mdXVyihyg1i2VnF67dm14fpXVPfzww1VV9dhjj223qdxPV0TX\nvJBMnaR0mncqA5UTXr16dZvWvGkeRhJsfXYk33Pkc5TWcz711FPbtNaNJ554YngtLacuraPoFXSc\nEz1Ctx8Ss3al00YFcq7prKzvROaiPuaso1E493GnGclCnSgGzj60vzJrU6P9+/Y7ISM/VEvXWUUs\n07T2q6O/k0xdmY1UQ9FRTmsTpAhwZMMgWbRjDSOpvpNWRrYosp6qjN2xqp5VH7fUnzkRwOh8Z2Vn\nvShoPaKoo7rPjJ2GjiP7m9YLsndpmuoXWf1pnB31G7P2NkXzdfPmzW1a59pkc6GlHxTqh0YRlmh+\nTVG3yJ6p+6htRe+P7F1LkcQ072RPdfoyml8davQuKguq3xRhSxlZzmejPzlzVIrER1B0utH4RxHG\nFK33agPt76xVt9snFX331PchfT8m+yJF0Ov1lNorWfMoirVek/o+mn9Q1FqKCNrzTG2X2KcPJdY1\n+vHwDQAAACAASURBVIYQQgghhBBCCCGEfPAJIYQQQgghhBBCWBvnaumalfY6q1p3CSXJnElyS5C8\nS+VlJJdV+dgzzzyzTat8TfPe5ZwqU7t8+fI2TfJyzZfarPRYtWXpdpXYqfRNZWqaR5IWdvkhRXdw\nZI7KKJLJLktRiXYhWWrPG8mVHQkr7aPWuENiVm6ozNhvqN1TeZLM1bE4OBLlmToya5tRnPrl1DvH\ndtXL+CJYmKhuLEVdnLWqOOPJGiIBLVnhTmIUtUaPo2flXJMiK2pa93Gip9F1+3nI2ky2MCdaEsmo\n9ZzEzJhHVoKl6DAnpSl6l47zOobPRjcctT16dmR5oDbozM0uIlSnyTI4E+2N2hfZjBQnUp/TxzqW\nH6XfE0VhpLReR+fUagNR+4S2fapTuj8tJTB6x6D71+dF7Yiipuk7gNq4yNqikYvU5qJlo+2ULG6j\nvCtk06O+4ZAg+4/Wl9E7TRXbn3u5OJEV9Zpk76OIbffff/8wv7pdnynVC6Wfh8YVLS+9jr4/qqVL\n+yGqL7Qkh74rUwS90fcCsl8rtNyGtindh8ZivZYur+JEXBtFMJt9l1Ao4ttSu98lCp8QQgghhBBC\nCCGElZEPPiGEEEIIIYQQQggr41wtXYpKmpaiFVQty4xJiu3IifU6KsVSiRZJ+AiVqaksVa/V5WuX\nLl3abrty5co2rZJUkrLpvar07pFHHtmmNdLWc889N8wjSQ5J9tslZvTstKyp3J1n5kiKT2vjoWdK\ncmiFLARadofEeVm6Zu1MZA0gq5djY3JsUUucVeSKWWuYQz92NgKHY7NxoqYtyf1P2md0nVkoetRF\nsLidBieSmo4P9BxHdgonWqZTLyhCkRM1hiTmJJ3u4yJFyyArNMn6qY5QuVN0EKcP63kj6T9ZpEn2\nTtYD3Ufl62oPoUhANJ7OtEmyDh3q+EhQvaC6ppAdazS3ctLErC2LrFYz0WFobkcWOM2L2myovupS\nBmo/0X7AiaAzejaOBZLSZMvSvFO702O1/ZIVZfQORZGmlqIG7qZp3r9myN42sro58yB6p9JnSEtT\nOH0JRaCm/rvXERof1a6l74+6PIhG7KI64ty3pundXhnZuGkZEm2z2o60nZLVXM85smXtXovmK6P3\nQ3rHpDmHQn3+7DIFUfiEEEIIIYQQQgghrIx88AkhhBBCCCGEEEJYGXfN0qU4UvulyAEkwSOrENl2\n9Doqy1J5l8rUSDJOUm+VlfV99HwqYdV8kcRP709lrmoNU6uXrgSv0lKyBChL8jHNC60eThY7uqYj\nX6a6oWWt9O0q/SN7F8n3aHV7J5rLvcJIMu7YHmj/00baOumc1CeM+hWqZ3QdR/arzFqOSKrfr0vS\nTydf1D+SJJ8sgdT/ntZW59jF6PqHilNWZKFQRuOiI9eftV/Tdj2PSqcVsgKPxj+KXEmRkO4E1MaW\nrGE0z9DtFN2JLDfUZp3tTn86Kkua5+xjO1ozznPs6dlxbZ9670QVo/nf6NlRVDHdTvMzx7LgzN+p\nDdKcfTTm6zl0jNO8qz1F7VcaiUgjc+l8n5ZVIAuYXmup3BVniYV9otZeRCg6stZHvU/dTlHgRmVH\nf6f6onVEbXz67qfH6runWqqcKM6jdqL39vjjj2/Tn/qpn7pNP/HEE9u0WiMp0tbzzz8/3K7Lmej9\nURund69+fxotS9N6T3rPlEe1eukz0PZF74cUiZneeXv7of5c26zaU8mGqmh+HQ5/NhxCCCGEEEII\nIYQQbiMffEIIIYQQQgghhBBWxoWwdBEzkXscOSJFtKBzqwRNJWAUFciRu4+kuSQdm7W6UVQTWs1d\nZYZkaaJ0zztZOajcFcdOoOeZtWfo8xjlnSwp+jxIYkgSaJU/HhKzVjSytC09U3qeToQEfRZUv5zn\nSFLbpcgUlC/CsZRRGRCObL9fV/elCBzU7kfW05PSZHckS8CM5cCJokSswdI1G4lBITvWKEoXWZL1\n+o68n6y9TpqsWaPnOBvVjvantGMboTxSuY/mK9THkeXKsZk60TNpXrA05s5aPPapvxcdZ65J+5Ad\nbjQ/oWgws3ZLp2/WuaPWC7IsjtqenlvPR21d0f3VwqIWDpqvOPZFmkf0/dVypfN+nU9QdC2yh+j+\nFJWIooNRWunlqueeeV5VXjS1Q0Lf3xSyylBEyZGdmNqaM37Q89Tnr7YhrYMK2ffIktnRtqNLf6iN\nS6N0ad1Va6JGfH766ae36WvXrg2PVej9lPqqvr9anjSqmG6n+koRwxSaL9K4SX3oqM+n7wB6Dn1/\n1HtyIrI5HP5sOIQQQgghhBBCCCHcRj74hBBCCCGEEEIIIayMc7V0OfIjR5Y8slQ5UUocOa3K6lR2\npvurvEolgSrBUmmWyvNG8kCymi1FEKriqF4k6yPJIclcSX7aceTadE0nsotCEkmSqJIMvj9jfdYq\nm6ToEWSnoYgzh8Q+0cUosszouZDckqTmZEuiZ0HtmixNS1bQWck+1cUZq4oLlUHfTlEDlH2ioFH7\ncmxq1Lcv2bQce5myhug/sxF3ZqLAzY6VTn0lawBFM9R9nHbS05Qvp305fYPT99D5l2zMZD0lWwfJ\nuJ3oTWcNSfCpvJz6e6i2Ecd2R3OVpTpI8z9tIzSnXhobdtOO3Zb2H12LosqSHULTOqfWCLNq4bh0\n6dI2rXNtslXq/I76x97etA2qRYss4mTR0WdN9htqM2SvpbF1KVox3TO9y5Al75Cg5RicMqL+e7Sd\n3t8cuy1Zp2lMpHZHz1fH3P58KY8UMY76HrJn0piv+aXxX9Mj2xdFztY+QPOu7+RqCdV8aV9C7/Bk\n19IyIwtuf8azz9GxcVO/QkThE0IIIYQQQgghhLAy8sEnhBBCCCGEEEIIYWVciChdFGmApFOjFavJ\nNkSSJz2frt5N0lKS3um1VA6m0QV0+0ieqeegFf81j7r/iy++ODy3plUGp/fnRC5yoomMIPnvbMQO\nkq/p+R0bnNLvT+W3ZGMjmZ4jZ7zXWZLpO1Y/kqo6Ulhtv46EcmQVpbqgzNoRyAYya90hqXffTnWU\noqbodkd+eicYRY9ac5Qfh9moSI5Vttdvp62RHJ3qAlm6aEygfcjWMGJWCu1EAqR7nbUxK0uWLieC\nINmvZ62Xs1HORudz9qFrOhaKiw7ZqxzrPNmP+3n0fDqHo/InGxf15WT5deZQmp/ReDJr66VxW5dD\neOihh7ZptXrp9cmarvNnipjV004UJZpzkiVU70mh6GsUvYssOEvlTs+ALDLK7PhzUdBnS1Y/KiOn\n/YxwliyY5az7deqDqc5RWstX26++72qd0nZKc3M95ygytu6r59D3bSdyofYB2seobVTPSX2lM6cY\n5cWJtkvtzrH0ElH4hBBCCCGEEEIIIayMuyZH2Ofr1dJXLfq7ftnUL9u6aJN+qaSF3uhXuJdffnmb\nVnXOrVu3tmn9stjRL5+k6tFfGjRfuj8teKVfXAn94kgLbS0tnEkLW9EvKgp9/aQv0PRLirOg5khF\n4PwKSb8+0/73Cqf9dZi+iDu/yjvMLlA5+vXEWfSV6r2TL2c7QW2vn4cW/nMW1KRftWhBPko7yojR\nM3DKYlYRdaiQKoBwfmXs+9AvhqRQ0GdIfaMDLdLuKMtG16L80i/x+yzA7vyCuBRIwFk0mu7DSTuK\nyVl11xKOesepY4fESG1exYvE0vxn9Lyo7KktkGLGWSxdrzX6ZX13H1LhaBCR0XG0mLejBNB5rP4S\nT4s2633o3Jzur6d1G81dnXkeKY+or6RFYmneOQousrSo80nX1DSN4YeEE+RDoXIepZ1ypnGbxhin\nz6Z58kw/7cwhZlV5qr7TNqt5V8WM7kNOHu1LupOF3hO1b9B8aZ3W9qjv07RIvC7yTK4eUkWNnqWz\neD69jxCz6vfDbMkhhBBCCCGEEEIIAckHnxBCCCGEEEIIIYSVca6WLkfu5sSbH0kuaYE0kpu++93v\n3qZJnveWt7xlm6ZFm0ayyipeGFUtWP1adH2VnWm5qDxU91HURnbz5s3h/ipz1bJWKdv169eHaZXw\ndWjhrscee2yb1mf37LPPbtMvvPDCNk0WgqtXr27Tr33ta7dple3pefSedHHrZ555pqq4XGixW03T\nAn6HKn9VHHnorGVgZl+SsNLCpbSoHMmxnQVQR9L7s1qQz5Fhkq2RbFwjme6SrcS9vrPYLrUTkqaT\nrPis72MN0BhDzFhlHFsPWaSdhVn1+mQTcKTOo/SsHdFZfJy204KedN/0DHp61qI12385C++ediHR\n2fbo2AMOFZ3naTk7i+eSFaSfh4JwUNuhfahtUF2nBcU1j9qWdY7dt5P1U3HGEr2OzvMoKIqi19W5\nLlnsluyWZEek/FLedf6uz0ytZk5/Nno/0HujcUOvqXnUeT8tqntIOMExHHvXyMZE89/Z+Y5jfd0n\niIk+3553slM7QX+oDVI/qOg7o+5PCzUrfTuNg2Tvonanx5JtlGxctKQKLccyCiw1G9jCsQE6HP7b\naQghhBBCCCGEEEK4jXzwCSGEEEIIIYQQQlgZ52rpoigGKlFSyZYTcakfS/YvPU6vr/ak973vfdv0\nm970pm36ySefHF7Tkb6pZE3TSpds0crcJBtVmZqWl0rKVHamdiaVtpLUWqWgek61QPW05kujnek9\nqeRXZX2aL91H70nLTiWEau/S7RTNTK1e3e6mFj9HTqn1iqSzZP07JEgmSDajJTuWI0EkOxXJr/U5\na5oi242iceyef8nSRW3Tgfohx1riRAob2b7ICuZYKRzLDcmIZ200o+tq+ZKlyLGQOFGXLjpLUSlP\ngspoFAnIkQdrXmicdax2s89lJHV2IsntE5GO0oozdo/Gltm6uI8Vdp8oko59bek4p93r8zgkdM6n\n8wBqG05fPsKJ6jJrVSFmo8OMxoHZiDRkQ6E5tdowdD5MSyLo/hQprd83WfqpTdGz1mtSFDItA3pP\noDmKzm97v0xLPFAUXsdKd6hz2tkIijPnPG2/uHvsbMQsqgszdk6KXkaWI01rW9Pz6Lyb2gZFvaL5\nsNblvr/WeZrf6zkoOp7mnZZf0bLWa+k7sb7DalrLo5+H7FrUHmfriUMUPiGEEEIIIYQQQggrIx98\nQgghhBBCCCGEEFbGuepoSR5JEjOF9hnJ1CjShSNtVumWWn4oEoBKxki2uRQNgWSYjkVM9yHr1o0b\nN4bbVZ6neVdUmqbl0S1dFHGAJPBk0SK5nZ7n4Ycf3qbVGqZSQS3LD37wg9v0SAqodUP/rtJsvSeK\njkIS4UNC79mxdlB7G9kK6O/UHinyjOaRLF0UpYui1lB61D/MrojvQLZNxYloNdqHZMezNoA7wVKE\nMa0zJP9VHGvLoeLYXej+yUrY6wPZFByciCGzkaOcc/Z8OhL0fdKOHdGJvrLUNqm8ZtNL/fBJxzqM\n7Ayjv+9ecw2RKwmV49O8TPehfnhkdaJ5kBPdiuZiTr2ftZmM8qb5ojIie6juo3NUtf1T9B1F96HI\nr0tRumgu4kQ60jk11QeFlgyguY5eq+eT5hCaX7KsndZueAg4tijH3tz30bpL4xq1dWV2HCKovY/a\nFUVpo7pA77JkSyK7lLZfzQNF0x3VRy13Wr5Dz0f2SbKy0VId+u5LNi7dZzRPdWzn9AzOqg2udyQO\nIYQQQgghhBBCuEfJB58QQgghhBBCCCGElXGulq6zipIykr45EVtUrqWSqx61qYptUSpZU6moSrDI\ndqX5HUUdIkkbyWZpFXa9J41KpWk9v0rcyC6jZaCRzbo8j+wGatciqbGWqcr9FN1HJbIkJ6Tn+txz\nz23T/Z4o6pMTFUfLi57ZIUH2J8dusBTpyrEaUNukKF0kvXQsKnQfS5bPfSIzzHIWkR8cab4TgcuR\n+y9FDNtNL1k+9rGeKGQjPiSce3AikozGQhofZ8uNnpFjJ6J9liyWylm1R8eupDj3NLKF0N8pTeOz\nbicr+6zVi8qylwH1B2RhcKKzHioUoYnmhTPRq/SZUCQXijCjcyWKuERzKCf6oqJ2pZ6mKFq6Xeuf\nbte54+XLl4dp3UfPr9D9UUTYkaWL5iLO3JzKmuZUeixF39V5Gln+Rn93ohif1Zh7UaD+yFnaY6lv\ncvpRxzrvWAMpX1R3luyRZNdylg2ZtRnReWhOQe8BPa3b9N30+eefH55Pl2LRNrK0REzV7W1N36F1\niRRN6/5Kfx5kbdX00lIHVZ5VkIjCJ4QQQgghhBBCCGFl5INPCCGEEEIIIYQQwso4V0uXsiQbrmKr\njO5DK/R3SJ5J0bjUBqTbacV9ko06URW6fM2JJqTSbZLV6T56H7TyOV1Xt+t5RjI0vTeKKqbPjqLv\nkKyOJGsUMUufq8r81NLV93csRSR1J4n9oaJ1XXGiwyyVo2PRmrGInbR91ho2E93JsSA4EWmcuu5E\nCyLbTe9jqM/UuksRS+g61H6V2ag8JHEfbXNkxGuLCkSyb8WxVI3qNNkUqO1QvpwoJFSPyX5E9qZR\nv0LHOTYnksM79iPHMj4qS7JrkVWY7smxgzn5ciJN9vJwosZRec1GZ7vo0PxP0xTJdCmSlpahzqdo\nLqpWJYpoNWvboCUDyJ7bLRRqpbh06dI2rdF09Bxq0dIIrFeuXNmmr169uk2rvUvvQ6F71fnaqJ04\nkTv12Ti2PmfOrufUZ0zPe3TfFPHH2ceJBnVIzEYjnZl/6TYaB50+jcZ2itKm7UfbuNYLshv2fTSP\nToQoxZlnKPTOpO1OrVn6HqLpft/6bkpLb+g+2q/ovZKli74/6FIvPUL17na1Xup5ejvVZ6R9Mtl1\naW62z9IE65oZhxBCCCGEEEIIIYR88AkhhBBCCCGEEEJYG3fN0jWLSrBULtplYiQ1cyxdKstS649G\npSK7FkmXVW754IMPDtNdqulI7DS/ur/K4WglcZXSkbVDIbm5Suz6tUimpnnXe9b7IxkxyepUyqby\nOd2uksdnnnnm4/Kr+1NUGr1nx7pE1rtDgmxpjtWK7FW9vc1arnS7ti+KZqfPXI+liBaOpWvUrh1L\nl2NzmrV+OpYu3X8UFUDvWSXiJBV1nrWmyVq7FIlml5nIPXo+57jZiAYXhVlpuELlvxSli9ogSdCd\n6B2jOlo1H2mq12XHjklRTaitk1zasQmSFXjU98xG5nL2p37WsSs7MvHe3zi2zpkIa2uBLFpO3ziy\nS5HFR+eWjo2L7ANk6aL5qB5Lee95UCsF2bW0jGh/Sus7gOaLrBoK9T29ztK8ZLZfc2xcTmRMZ9xc\nguYQzrkPddwkey7Nm+jYUdQrx8blWJ6duTFFZdR5r2MR7mnH1qvnpmVANK370/uxpp0lVTTd3/f0\nOLJm6ruhWj9pCQRaVkHPObKX7aa1LEf95iia4W6arIf0zjJLFD4hhBBCCCGEEEIIKyMffEIIIYQQ\nQgghhBBWxrlaukiK5KxsTjLELpdSeRdFGyGZusq7rl27tk3/4i/+4nAfReWken6V0T788MPDY/v+\nes8aiUBlvHpulbqpBe3pp5/epp999tnh/nofjpVM99E8dBscSUXVavbII49s0yojVukdyS91H4ok\noseq9E4teWrb6+VN9hi6DtnhVNan9eGQcKKnkLyZrAe9vjhWOLJeUDQ0klhqXVfJ6Ui6vXut00K2\nBpIO06r8FPGFoqYsRYghS9esZN2Bnh/1D07UjBGOnXZt6DN3oh+RlYGigIzO7Vik6DrUf9IYThEd\nHYvDEo6li6J90PUVshXSfYzqOuWRZPok8Sd5vtPPOiy1U5pP3IvMlsXI2qvPiqIzkXWLInM5NnrH\nlqRoHexzVr2+2q80rVB+KbIOtVnFsVguWbfpuNkoRo5V1YmmR+l+3aV7O2n72qD+m+ZiFHlO9xkt\nB0Hvr2R7dKzTtDSBvg8ptPSBvh/2ZT7Iiq+WUH1/U7Stk72Llu3QPJJ9TOfvGg2rn5+sTTQ+kv3Y\nsXTRM9DtFGVvNPd3rJ+K8+4125aj8AkhhBBCCCGEEEJYGfngE0IIIYQQQgghhLAyzlV3S5KqWZm4\nSpq6BIvkXSqdIomnyrjU0qUWKZKoUgQqtWNRZIIuFdSyUPvTpUuXtmktF5W6qcRPI1GpnUn30fPo\nPVGEB5IljqSF+hxVmqcSOz03WaH0mnpPek5FnyVJAkdRvVQ6rM+FLCkk+dS6Sfaeiw5Jtx1ZMKVn\nzjcbQYdklbRd6+BpbUyO9NKJ0kWWF+oHHSus3nc/ls5BUlGSi5PdkSKMKSRxnrF06d9nrDJrgZ6d\n4tgQRu2KrJzUTp1n4Txnx+5IkSx6v002F4poRNvJJklzBIXum/rEfn9ONEfq+xzrHVk4nehrxMhG\nQ+37tBa8Q4PKjeT7CvXPoyhdWtdH9t3d9FnZBE5r+yNbh7ZBPTfZVnXepvM5p35RpKOlKJ1OVDuy\nCFFeqG1S1CGKtKTWEt1/ZOmaHSuIQ22/ZDOiaMI6Jiij+SW1aa0vWtf1+dNclPoSfaf5wAc+MMyv\nHqt2LI3W3N+lyBqp96nvg87yDRTZmMqJzkmRv5bGS7KLaZ9BcxGa0zjthOYIo/d87QdpaQKtGxSV\n2JmXEIfZkkMIIYQQQgghhBACkg8+IYQQQgghhBBCCCvjYEIpqAxvZNOiv6tkTiVVKhEjW5RauijC\nyWOPPbZNX758eZtWea3atDTdZV16PpXpkVXp+eef36Z/6Zd+aZtWO5pGpdKIXVo2jz766MflZXcf\nijrVJWYaLYmilJF1ayR130XPT9fS86uckaSoXQbnWFgcyTzZ3g4JfV6O7JvucyRL1bIimwKlSb5I\nq//TPmT7cqKTdZxIPWRtItk3bSd5Pu2j6Z4HJxqYI413ohXR/s72ESRvJkvKvWLpcqJ0zdi7yFZC\ndUShyD5kbVYr9AMPPDBMU0QflZj3NO1Lab2O9g1OFKXZaBgUcaWXmSMvp37Fsc859jKnz13Cyfua\nrZfTUVKM/rZvdyLWKjQ+k4VI501kbaFr6bEjuxSNq87967l1aQIdz3Q8X5qj7uZxyfZEbYEsXU5f\nSf2B82woUu1oDrZPBC6nvzkkRjb3qvnnOLIZU71w5nkKtVmtg/reo9BcU+uOvs/28zjze30fcGz/\nFBWS5p00R6H5XT+PYzV30rPQdanOaPn1ORAtgUDlqGm1d5F1zCEKnxBCCCGEEEIIIYSVkQ8+IYQQ\nQgghhBBCCCvjXC1dtNK0QjI8sjp1qRWtgK1SKJK9qw1I5XtqhVJZpe6vkrnHH398m3744Ye3aZWV\n6330/FB+n3vuuW1aV1t/5plntun3ve992/RTTz21TasMkKIbqL3MkXeP5Kq0erqeg1bLJzmlE0VI\n65I+D91OUt9RFAyS+9FK9Aqtsn5IUPtypP7a9ujY0d8dixhJa7Ueqd1DI9s590H1iyTpSzgSy1kL\nmGPB0mfQt49sXrv7OhFfKC8k+z4LSS3t69ib1oYTsY0iYC5FjXPGYSdfZAOmSJAUFVItYJoeyerJ\n9kjtxYm6MRspj1iKYujUXbJFOf0B7U/1gbYvjZGOzdXhUCMBzeLYY5fKgsZNiuCkFg+KnqXnJEuX\n5l3nRTo37mnNC0W6UrTP0vmcLlOgdVHvSe9DofF8KcoN2a8Up79xbJUUSYyiHjlRnUbQkg1kbXVs\naofEbOTXpbHCsVvSuw5FV3Wi0JK9S6GoV307RbTS42jsI0uXM1+etT4qS2MPtUfHmujMNZ20onOX\nkR3NWc6C7F37WNMOvyWHEEIIIYQQQgghhNvIB58QQgghhBBCCCGElXGuli6VjJEETLerZJusMktR\ngUjeRnI0jYal59btek61S6kFS60lDz744DY9klDq9fU+NdKWSlv1OhqxS9Mk41U5mNrRSM5IFqme\n1vORHJ7k4iSHc2w/WmaOtG8kmyPZIqXpPmhV+kNC2wbdP8kNSZLYoedDZUXPRWWSZ4Vzrx3H9uBI\nVR0bhuJENhnZWxyZ62xkMEfe7dhflsqMyoVsmrPleEg4fcqSTWH3PKNx07HLkSWFbALaZtW6RZG0\nyN6lNpNeB2hcU2j80LyTVXcflsYwsngQFAVNy5rK3YngNookVjXui2f7gzXjWFYd69bI5uGMlWTp\nUluU0070WG1rNFbodfVa3XKi80+K0kltRG0rNL/UeTLNCxybyegZOJYNZ9yk/RU9P0XgornuKOqR\nbqN8kV2bLF2HCj1Hin6k+yxFTKN3WWovNPbqsyDrI821Fcf21/NA0TWdKFqKE4mRxidNO3blvn02\nkpwzL3QsUmTHcqKmjvZ1rHzUbzoWbeLeHq1DCCGEEEIIIYQQVkg++IQQQgghhBBCCCGsjHP1n6g0\nzpExk8xYGUklySJFMjk9h9qcrl+/vk2rbPSDH/zgNv3AAw8M05cvX96mNSKJyte7nI8khpQXtZGp\n7YusNRRpQ21iZHfT+9b7G0VHm43u5ERBIdk5RTGgSBIjKaCzyjxJcclmotc8JLRtKvQcHQnpKFrU\nWazOv3v9WXsEsSTPn43ANbuPc/6lqEt0fidCwmz0H8WJvjITCYhkqxR5zLF13issWbeqlq2XtJ0k\n4GQNoMhcTlqtJRQ5qKP1T8cGx058VhHh9DxLfSVF5HHk4lTuFOGM7NqapggtSr8Px/IyOm6NaPlr\nOVOfpSxFJh3ZMao4+pPO4TRN1ycLy8g+uXtdvVeN0tXnozqfoPpNFhZN63moLeu9OixFT3LqN5Up\n4cwLZqMejc5JfdDseL4GaEygOqVtQNNqMex1nfpUKn/tj6kPno2sSNYwsk6NlrIgy7Xus7Rkwy5k\nHyQr4cycjuxoFD3MWZLDwRn/yQbXt+8T7UzzTlZ3hyh8QgghhBBCCCGEEFZGPviEEEIIIYQQQggh\nrIy7FqXLiZDkyKi6HMxZRVtleioDJRmeSlU17UjvSCqn20eWLi0jTev1VZKo90T5Ihm+lgFZdx56\n6KFtemSVIGkePUeVrynO6vPK7Cryo3pA90xRSpwV4melvhcFlX4qVEbU3rQ+9O2zVj/HGkF5tn2F\nsAAAIABJREFUmbUbOM/6pG277GP7omNnrVZLeZ857jT5Jehao+1Ovoi1WUgoQqXDWUj2qd8jufYo\nEuVu2on0tGTn1TGRIghSlEnq76hfc6TsVNaj/smJJKpp3Yck4M446LBkRyNbDuHsc6hoe9A6pXM+\nsgov2cG03qjVUeeQFL2L6hdFvdK6ptfSNqPHah0YzUfJ2r4UAW53O+VX74neE/ScVE6jCGbU7yhk\nx1O0jOi5z7ZN6ov7dmcpB6e/XUP0PbJd6bhB5al1WqPQ9XZC80967yK7J9VLqi8EjbM0nnVorF6K\nWFvlvcM7ESLp3Wtm7kIWKWee4SwtMhula5R3shjS0jUUXVHHFk07HH6rDiGEEEIIIYQQQgi3kQ8+\nIYQQQgghhBBCCCvjXC1dCsm+HGvPSHpG8i+SH5OMS+V2ugI2RSVwpH0U6aDfh8oHyZZFeddz0+rv\nzirgul3vT8+vUuJRJAmV8ZI0TvchaRxJMfeJgDSC6h3JX0neTNLZQ+LBBx8cbid5M0kcR3WAnrkj\nnXZw7BYOd8MK5MjaZ8+zFKWLZLOz1i26pmMZc87ZobFitq1pnb1y5crUsXcTJwoNlcWS7c6Rjjvy\nbudZONJpisSosvo+Dml+SZquY/is7J3GTRqTHOtlv28aNzW9FCmm6vZy0XmE1hk9D0nfSWI+6rtp\nHFCovM6qr74oaP2i50/RaWh+N7Jwqs2K7GKO5ZxsUTQHprq+1E7o/hUnShyVHdm+HZbGLWcpCTqH\n877hpGmpCCqDvo9en5Y0oKhIxKHOael9hKyMCtls+zmpnJ1o0voMtS3PRjOmd2KyDM60E+qPnHdo\nYnZ5DKU/s9klIeh9mvand2hnvqLofGTUr9A46NjeKRqnQxQ+IYQQQgghhBBCCCsjH3xCCCGEEEII\nIYQQVsaFs3QRJKHrkirHLqDyOZJRk/RRr6/nJym0QlaNvt2xbqmk14nmQ3J0knnOSvVH20kqSdI4\niqA2Kw+kSBm0Sv7oOhRVgqSSJKU+VMm6E6WLIlNQ++nb6TiSTzqySn2ezsr6s4yOpfM5q/870QLI\nEuBIUWeiG5BMf6at7x7r2Lgcm9qStY+etdNnHGr0LuqbFHr+S1EkRmPpSZClTvNIlgy1HGlf+uKL\nL27T2g9RX97bgyMRdyL+zEYCVBz7yWjcoHGYrF46nupzIusWRSTV7TR3WYqyouXrSNPXYHkm7r//\n/m1ay1Drrm6neqHluGTporFaoYh0szZcxRkH+nXp3BStiCxdapnT9FlFtxq1TSeqrOL0H7PWZloS\nQstAz9/3IXu93hOVKdkND3XcdJb5oLFV66Pu0+uDs/QIPSuyGTnzXrIM0lhF/XDnrGxZznhG4y+9\nn47uiZ6dE/nMeQ92xiennBzrWYeiozlRt2fH0yh8QgghhBBCCCGEEFbGuSp8nF+2aTE2/WJGiyAv\nnVu/iNJCcktqnN1zOl/y6Ct+/1KnizA6Cz/T13e6zugL9e52KkfaZ3Qtel7O4mn6q5ZzTdrufH3t\n16XFhB11FP0aQl+XLzqOSsb59Xu0D9W5pV9RTrqOo96ZUb3sXmvpfArlhb7Wz+adoF8mRsfO/mo7\n+8sB3avTnyqjsnH6WEdZd6i/VN5JnDLR50m/eJMyVft16hvpF6ulBcUdtRf1686vqTQvcfp+WnS1\nj+NnpULS+9P+lMZfWqiXnutorjO7SOmaeeihh7ZpGsNI+aNpfRa9zWgZqjqdfhGmvlYX9nR+2da5\nJs21Z9Sreo7Rfe6maa7vBB6gsZWUVaM+iVT+jsqPxiEqIypfWsyX2lU/DymvNV96bk1Tuz7UcZNU\ndo5yc+lZaz+qab2mKnwclS71GYqqNfU+aPHekUKfxlUav5zAIvQ+dtYBVWbf05TZ7w+kQnLmHaN9\nnMWpKY+0mPOsi+HeGJVDCCGEEEIIIYQQ7iHywSeEEEIIIYQQQghhZVwISxdtV7mSStZUKtelUWRn\nUkiWRRJWR8pIUnaFpLM9z7ogH53PsW7psXodLbvRIoy76Pk1b1o2/fx6HVrgl6xbJKt35GskOSRp\nIcnjR8c58l+Vbjp176Jz69at4XZqM2QrGFnz1LLoLETqWABJEjm78LGyZGPaZ7FlZ4FMsoc456T2\n0yELq9Nmya41szDdLjP7zy7ovTYcSb+zOKIyquuzlmTH9udIukm+vmSVpAWOSRrvSOaJ2fGB5PEj\nS9doXN29JrU7hRZpJRn8rD2v49THe8XSRYs20xhGiymP9tFnTvMwGoe1/jl9v2Pp0rTe32gM0+dP\ni0brXEEXdKd5rNOvUR9GVpvRM3AWo3WCeZANlBZ3pzbjzP2XLF2Kvg+QpWs2qM5FhOrd7NIeo3kG\n9an0fKit0QLhVObOIvk0Xxy1TW0LNA7pNek+tE5pXqgfdBiVzT5jO1mqqN7T3Jyg5zp6Vz6rJRZi\n6QohhBBCCCGEEEK4x8kHnxBCCCGEEEIIIYSVca6WLpVaLa2UX3W73EzTSpeYkd2E7EmO3JHkp07U\nC02TvLvLtBz589IK4Hq+XTS/en+PP/748Fh6HiOpHMnOSdZHMjmNdkHndyJSUOSRUeQHkkbrdpVs\na/3RNNWTQ+K5554bbifbDm0fRd5QS5f+XS1dZMlwbENOdBwnsswo2hvJu0nGTdekaBxk43L2X4oQ\nRPXSsYgpjoVjVq5L0uSZ6GCzUdgO1WbiWNfIekDjUIekyo4d8U6XJ9mS+rOmyBxOm9XtjoWUxh4n\ncuFI3k33Rnl0LF009jmRe5z5RWc2yuChtjsHnU/pXJAih2q/Tsf28iWbFUXkoXmv1imyXyvOeLa0\nrIDmV+dKjtXMsbbM9olk6RpFPKO6S+ejua4+U3qWeqyzxIFuH1lzqL/X66uNS+e3CkX5OyScedZo\neZDd9KiO6LYHH3xweE0tW7oOLbHhvMvRkidLFmHH0kXXpDLV61M5OsuJ0Lg4E6WTrFuONZ3mUTRG\nO98dRjgRa513llnWOxKHEEIIIYQQQggh3KPkg08IIYQQQgghhBDCyjhXSxetmu5Ifkki2+VVjkSM\nLBaKE3WCZOIkzSKJXb8nldWRzNqRgBEqydNy1O36bChKwqhsnKgxJCFUaKX7fSwEJMkbnY/kgyQv\ndqKzHRK/8Au/MNzu2Li0Hml6xtLlRDghebdj3SKb4tLK/dR2tb3oPks2q93tJHEnSxfJwUdWr1lb\njhOJ4KzquiNjHW3bJ++HGsnLsdCQlJ8iC/btZCFyIk455a9txrE/ORGl+j5qmVCovGhco2Od6DTU\n31B6VAdpTCYcKxaVnRPlbqaNz86XZs9z0VG7ks5tyDrnjBujuqnnVvvErE3BiZpD4xD1A6P5pd6n\nWogcCwnZER27vrOcg1ptdJ9+HmovZGHR+9BjNfIY2frouVMUWLLX9HKlZ02WLk0rjq3uouP0TVS/\n9fmOxhMtT6ovdG5ltj+ejZJKFqXROWhMpMhVem5a2oTy6FgyR+3dicZF97FPPXaeE73z9vTMnLfK\ns0XPWr0Oc5QNIYQQQgghhBBCCEg++IQQQgghhBBCCCGsjHO1dJEsiewLtCq+0qVyJAM9KxvQbAQq\nZSlyj94brdQ+a+ki+avmReWcs6uZ930o8priSOno+RJUNo7McfR3JzKFw6HaRt7znvcMtzv2gSVL\nF9m4dDtZOWaeZ5UXgYr2GfVDZG2hCIIk49XttP9seikKGEnmHYuOQm1tnyhZJL0fncd5prP2m0OF\nypnsWBSRpve32u9S5JlZyyLld9aeoTJx3Uf7kCWovGjconpJdceJCDITmdOJwKX7UL/pWNPI+rbU\nzzqR3Wi+5NSTQ+Ly5cvbNEU20udCffnSOEfHzfa7mhftG5xIYrSswsjuQFG6aBzUNFk1yEpB0X9o\nrkt9Yr8utRcnuhPVAadf0fPofeg8iZYS6OVKYyzNFWiJBcdKf9EZPdtdnHIZjXmzkQ+diEtk53Ws\n1mofJKvz0rmdaLDUf+uYrNd33ludsa3jRDIj+xUx+87mnH8UIY/aN90HzbuX5ssncfgz4BBCCCGE\nEEIIIYRwG/ngE0IIIYQQQgghhLAyztXSRdJekoxTRIORPE7PTXIpJ5KLE11B9yFJJEnfNT/9nlQ2\nS9GySHbmrHZO0jCSv5IUcSQl0zKi8iWZq0IWApKTLq0+X8Urx4/OTZYyR3rvyAYvOu9617u2aUc6\nTdtH9i6yZlBb2ydSjhN1iNrmyI5FfZBu1/ZLbZkk6xQZwrG4jSKM6PaZfau8qBbKrPXxrKP1zEp3\nD7WdOhGPqH6TtaannQhos3JiZ8yl81MkrdF56J4dWxjZyyjttI19LE2jfWejkCiOZNyJmjZi5hnt\nnnttXL16dZvWekd2ZbKQLNkmaL5DNj5lNmqNE5lrqZ92LKF0H8Rs1FqKDkvz8Z4f53x0/2RVdWw5\nZFGm9Cg/Tn/rWHSobzgk6Hk597MUicmZSzj9rmOrdd41Zp4Rza+d90dNk2Vx1jpPVqeZfWetXoqT\nX1r+Y2Ysdt5lZ6OHOt80brvW1N4hhBBCCCGEEEII4cKTDz4hhBBCCCGEEEIIK+OuRelyIomQRHok\neyKZItmWKKKUyk9ptXOKqqWQVWMki9X7n5WpKbNSRZIKzkR+IEsbXZMiB5E0zYne5VjWVGLdnwfZ\n2Jzr7FN2F5F3v/vd2zRJTp3IDSP5sWMFoygWTtQ6soFSn0CS9VGbVVk2tWOyXDnRdMiKSv0Klcdp\n653T3zjbT9t/7O6/FKVLofpAHGrbdKB2RRahXl5aJmTVcSLJ0DjryNGpj1myHM3K2x0bBu1/1nXH\nOR9ZT+g89Kypr9LycywPfX/Ki46xNHdbQ6Q85cEHH9ymKRoX2dh17jSKIkUWHy1nnaPuYxmguTk9\nuyWr16w92MnXbCRZOs9MHXSWUqD99Xk4UTqpb52x68y2u0O1OTs49hgaYyjS1KiN0Txv1mau/QfZ\nj52o0EtQvThtG9ll9j2UxqGlc9JzdOaWjv3VmV/P2GjpmwNxFhbxXdY1+oYQQgghhBBCCCGEfPAJ\nIYQQQgghhBBCWBvnaulS2SpZKVTu6EjDu9SJ5FcUFcGJPKP7k3SLZLxkMxlF7iFpGkm69pH1ObJB\nx0azJN2dxblvxbG2vPTSS9v0yHpGEQ+o3pFkep8V6i8KN27c2KadKAIzkQNmo8HMRgsiOwJZw85a\nxkwSUifvjnye0hQJZWTXmY3GRDj7O7J6Yqk/u5M2m4vKrN2UbLu6z1LbdNIKtUHHKnTaPDj9Co2t\nTlQgZTYCEtGfx6wUmyC7wUzkE5eZe6Wx8qzu+6JA81WF2sBSpEfHiueMp/rc9JpkkXKicel4szSv\ndvoMZxwkWwOdc5alvDt2dMqjlpG+B5Gli865ZIudnSPNRmY6JGajGS6NlVXLdWQ2wiydh8Ynygu9\nTyujuuNYhWn7bL2YLZslG/dZRY9z7GAE7eO8w3acfpuebyxdIYQQQgghhBBCCPc4+eATQgghhBBC\nCCGEsDLamldpDyGEEEIIIYQQQrgXicInhBBCCCGEEEIIYWXkg08IIYQQQgghhBDCysgHnxBCCCGE\nEEIIIYSVkQ8+IYQQQgghhBBCCCsjH3xCCCGEEEIIIYQQVkY++IQQQgghhBBCCCGsjHzwCSGEEEII\nIYQQQlgZ+eATQgghhBBCCCGEsDLywSeEEEIIIYQQQghhZeSDTwghhBBCCCGEEMLKyAefEEIIIYQQ\nQgghhJWRDz4hhBBCCCGEEEIIKyMffEIIIYQQQgghhBBWRj74hBBCCCGEEEIIIayMfPAJIYQQQggh\nhBBCWBn54BNCCCGEEEIIIYSwMvLBJ4QQQgghhBBCCGFl5INPCCGEEEIIIYQQwsrIB58QQgghhBBC\nCCGElZEPPiGEEEIIIYQQQggrIx98QgghhBBCCCGEEFZGPviEEEIIIYQQQgghrIx88LlLtNY+qbX2\nF1pr72ut3Wqt/T+ttS8+/tvva629JP8+1FrbtNY+6/jvP7rz919urb1r4tqf2Fr7K621f3J83t+x\n8/fWWvvW1trzx/++tbXW5O+f11r7qeN8/0xr7beeUbGEcBC01r6/tfbB1tqLrbX3tNa+cuLYt7XW\nfqy1dq21tpk9d2vtvtbadx0ff7O19rfP4p5CuOicNG4e//0LWmvvPh4z/2Zr7Y3ytxPHNePan9Na\n++utteuttedaa29vrT2+k7fvbq09c7zPO1prrx+c57cfj7vfsk9ZhHCItNY+tbX2kdba95/y+L9x\n3H5eKdu+prX20621j7bWvndn/xPnuyGsHWofrbW3Hm+/cfzvx1trb5W/7/uu+eRxm9NzfIP8/Rtb\nax/b+funHP/t0dbaX2qtPX08z/27rbXPPqMiuSfJB5+7xyur6v1V9dur6lJVfX1V/WBr7cnNZvMD\nm83mgf6vqv5AVf18Vf3fVVWbzeaLd/7+k1X19snr/0RV/f6q+uDgb19dVV9SVZ9ZVZ9RVf9KVf37\nVVWttStV9Y6q+lNVdbmqvq2q3tFae3jy+iEcMn+yqj5ls9k8VFW/u6q+pR1/kDX4WFX9YFX9e6c8\n95+vqitV9RuO//t1p8h/CIcIjputtUeq6oeq6hvqqF38dFX9ZTkWxzWTh+uo7T1ZVW+sqltV9T3y\n96+tqs89PvcTVXWjqr5DT9Bae1VV/Zn6/9l782Ddsvs8a32WB8nu7nu7+96ertSSW6MdCwfLMVWO\nk4ICO0FFKkWCwalUWUAxVFKpgkogxZiZwB+JcUhCTCgDcUhBIISQSjChbCYlxjgmjiwJ2ZJitaSe\n50Gt9vzxxzlr67lH67n7t8537ul79n2fKpVW77u/tddee017n/ddv9b+n4nrhrAl/mxr7e+e5oe7\n3e53tta+avBPT7TW/lhr7b+Qn95ovRvC1rH+8URr7Z9rrV05/t9fb639t/0fz+hds7XWLiOfP3ri\n3/4yr7Hf73/u+Pgd7Wic+EA7ms//Qmvtb+52uztOcf3Q8sHnDWO/37+23+//0H6/f3S/3//qfr//\nG621z7Sjxn2SD7XWfmi/34/UAO9orf2G1toPTVz7F/f7/ffv9/u/3Vr7Fbnen9zv94/t9/vHW2t/\norX2zx//27e31p7e7/f//X6//5X9fv9ft9aeba39tur1Q7jo7Pf7j+33+y/2/zz+3zuLv/3Z/X7/\ng621j8/mvdvt3teOPgL9K/v9/tnjPvj/HnArIVwYVubN39Za+/jx3PTzrbU/1Fr75uM+09qN57XK\ntX/4OO9Xjvvnn2mt/Xqc8vWttb+13++fPr7+X26t/ZoT2fy+1tr/2lr7mclbD+HCs9vtvqe19lJr\n7UdP8dtLrbU/2Fr7/Sf/bb/f/9X9fv/XWmvPD/5tbb0bwqax/rHf71/a7/f/YL/f/0prbdeO+se7\nRnmc5l3zEPb7/c/t9/vv2+/3Tx6vc/98a+2rW2vvPY/rb5F88LlF2O1297fW3tNOvAQeS9J/Y/NO\n9r2ttQ/v9/tHz7A4v6a19hH890faly9cya619k1neP0QbnmObVVfbEcvb0+21v7nc8j721prn22t\n/eFjS9dHd7vdbz+r64ZwkTgxb143b+33+9daa59uX5q7Zue1NX5ju36+/sHW2q/f7XYP7Xa7r22t\n/c7W2g+jrG9vrf2LrbU/csA1Q7iQ7Ha7u9pR2/+9p8zij7fW/lyLSieEM2W3273UWvv5dqRI/eNy\n2iHvmp/d7XaP7Xa7//JYiUt+y7EF+uO73e533aCMv7YdffD59CmuH1o++NwSHMu8/1Jr7S/s9/uT\nf/nrnewz8vPvba39V2dcpDtaay/jv19prd1xvN/B/91ae3C3233Pbrf7qt1u96F2pD742jMuQwi3\nNPv9/ne31u5sR3/1+KuttV84h7zf2o4+rr7cjmwjv6e19hd2u903nNW1Q7gIDObNk/NWa0dz153H\n6RvNa7PX/odaa3+gtfZv4vCn2pHd7PHjvL+hXf9x5z9prf37+/3+C7PXC2ED/NHW2g/u9/vHZn+4\n2+2+tR2p6f702rkhhDn2+/3ldmSR/j2ttZ+S007zrvlca+3XtSML9Afa0Vz8l/Dv/107mievttb+\n5dbaH9jtdr/jZCbHH4v/YmvtD+/3+5NzfCiSDz5vMLvd7ivaUUP+xXbU2U7yve3Iuzj67Xe01h5o\nrf0VHPt3sPnVD+x2u4e5IVaxWF9ord2F/77UWvvC/ojn29E+CL+vtfZ0a+03t9Z+pLU2PYmHcNE5\nlpr+7Xb0IeZ3ndjk7nfurt+A/YfX8rtR3seHX29HewD9sWOp+v/ZWvvfW2vfdYa3FcItjcybJ+et\n1o7mrlfl35d5bWbe3O1272pHyp1/bb/ffxj/9Gdba29urd3bWvu6dvSh9oePf/NbWmt37vd77ikU\nwm3B8V/n/4nW2n88+LcbzpnHff0/bUf97ZfPu+wh3A4cK2J/oLX2Q7vd7j7+22nfNff7/Rf2+/1P\n7vf7X97v90+3o7n6u3a73Z3H//7/7ff7J47Xuj/Wjva3+2dOXPst7Wjf2B/f7/f/4c2rge3zleun\nhJvF8V8Wf7C1dn9r7YP7/f6XTvz7r29Hf8X/K4Oft3a0J8Ff5V8M9/v9H29fLsmb3eTq4+1oY8uf\nOP7vb26Qrh+/ZP664zJ+ZTvaUPpPTl4jhC3xla21d+73+39y8G9/aXBsOu/j9E8P/v3L9vYKYavc\nYN78eDuaE/t5X9eO+s3H8e/Dea06bx7bsn6ktfZH9/v9Xzzxz7+2tfbv7vf7F47P/dOttT9yLGH/\nx1tr37rb7bod5VJr7Vd2u9379/v9b524/RAuIv9oO9rs/HPHgro7Wmtv2u1237jf779lcP4yZ+52\nu8uttW9trf3l49++6fifHtvtdt994qNrCOH0fEU7cmtca609g+Nn9a7Z16omNtm3oy1CWmtHkS9b\na3+tHQkKZgIshAFR+Lyx/Ll2JGf7Lfv9/vXBv3+otfY/7Pf7V0/+w/FXz3+2ndLOtTsKIfvm4//8\n6t1u92ZI23+otfZ7d7vdtd1RWNnfx+vsdrt/+NjOdVc72vjy8/v9/m+dphwhXDR2R+Eiv2e3292x\n2+3etNvtflNr7Xe04kaUuyPe3I78yO24731NMe//q7X2udbav73b7b7y+KPwP9ZaS/8Ltws2b/6P\nrbVv2u12v/24f/3B1tpHYJO+4by2xvFv/rfW2p/Z7/c/MDjl77bWvne32106tpv97tbaE/v9/rl2\nFDnsPe3oo9CvbUfRUP7z1tq/UL1+CBeYP9+OPr729v8DrbW/2Vr7TYXfdvty/+0Hj49/oB1Huzue\nC9/cjj4Gvel4TmXY9hutd0PYNNY/drvddx6/z73p+H3u+9pRdMlP4Lenftfc7Xb/yG63e+9ut/uK\n3W53bzuyNf8f3Za12+1+6263u/t4Tfxt7SjS5f90/G9f1Y7EDq+31j603+9/9YAqCC0ffN4wjv9S\n+K+2ownsKUpaj//9ze2okw3tXO3IVvVSO7JznIafbUcd6Vo7ell8vR35LFtr7T9rRxK6jx7/728c\nH+v8/nbkzfx8a+3B1to/fcoyhHAR2bcji9Vj7Why/BOttX99v9//9eLv396O+ltXHrzejvrjat7H\naobf2o4WvS+3o5fG7x3s/RXC5rjRvLnf759trf321tp/0I76zre11r4HP1+b19b4l1prj7TW/pDY\nvf6NdrTx5afaUeTKD7bjuXG/37+63++f6v9rR33+ta4GCmHL7Pf7L55o/19orf38cZ9d++3+xG/7\nb57e7/e/eJz+99pRn/q32lH49dePj3VutN4NYetY/7jcWvtv2tFa8h+0o4+yv/k4ymTnkHfNR1pr\n/0s7slV/rB3tRck9er6nHW3C/Go7+oPMf7Tf7/s777e31v6pdrRdwUuYc3/DKcoRWmu7/ZdH+g4h\nhBBCCCGEEEIIF5gofEIIIYQQQgghhBA2Rj74hBBCCCGEEEIIIWyMfPAJIYQQQgghhBBC2Bj54BNC\nCCGEEEIIIYSwMfLBJ4QQQgghhBBCCGFjfOV5XuxDH/rQEhLsF37hF5bjX/EVX/ru9Iu/+ItL+vHH\nH1/Sv/RLv7Sk77zzziX95je/+br/b621t7zlLUv6K7/yS7fI6/zyL//y8Dijlv3Kr/zK8D7e9KY3\nDX/71V/91Uv653/+S1HteC3m2cvGMvI+ePzjH//4kv6xH/uxYd5f93VfNyzL1atXl/TDDz88PP5V\nX/VVS/quu+5a0vZsej3x+nxGv/qrv7qk+bxeffXVJf3KK6+0Ec8///ySfvnll4dl4f2xzi5fvjw8\nzvvrx/kcd7vd8DrWZpi2snz/93//lzK9xXnnO9956nB9rLtR32A7/pqv+ZrhuQbHiQrWNw2ewza7\nlnel7LOwLGyvvJYdJ71v8n7YNznGsX7ZpvlbHueztvGxUu/G6Bnw+hZV0spifOITn7gwfXO32y03\n/d3f/d3L8e/7vu9b0qzzp556akmzPjl+9+OsT/77a6+9tqS/+MUvLmnOa7zm137t1y5pjsF33HHH\nkuY4yTmav2V5OQ8888wzS/r1119vrV0/lly6dGlJc75hGdnWOQ9xjuF9syycEx944IElfffddy9p\n1qWtL3odsOw297DPjube1q6vO9Y18+EzG60/Wrv+eRCew/QI3oeNE0yzjCfWaRemb/7oj/7omYS5\nnRm/Zsc6W+fYObPXHa1v2deYZju2NbL9lufwtzZXGbP1N5OfvT/YNW3NbPnb8+vHbf1jfdeOW3v4\nU3/qT12YvvnhD394eRg2z9l64rRrPZ7LNmrn2PqTz4XPnOdYW7B7Gp0/m5+1RRvvuV7ltXjflev2\ndGX9adchNify2VQimFuf5X339sZ2VxlLCd/tOeezjN/1Xd+12jej8AkhhBBCCCGEEELYGOeq8OHX\nOftrGOFfnexLXf/Ctvbl+2TalD+E57C8dr4pHda+0PM69td0fuG7cuXKkuZfJPkXVF52AuQWAAAg\nAElEQVSfx00hwL84sjwsO/8aMTpmX1Z5Td4Hy25ffPtfc0+Wy1RZvJb9dbKn7S9fFZWItbez/uvR\n1rC/hhmVc0jl6z7zXFP1nMXvqlibtrFyrW4sj5tR9nA+3EAVcap8bBwzNSPbkc2npujj2Mw5ycZ+\n/pZrgX6OqXp5fHYs5/mc2/hXtcpf2/jXPNLvm3VhitLKX0FZj7N/xefxmb9iW1kOOX92nL+dsXWL\n9c3Ks11Tb81ia0hTmLHs9lvC/sN+WrmP2fZ7WmavY/daebfpsF4qqnVrGzdDwXze2LufrbPI2jlr\n6uqTedg5TFfUJXZPBtd6vW0cMtZaOzLlZuW3pnIa1aWNd5YmNsZU6t3uyZS8o/df1hHvszKez5bL\niMInhBBCCCGEEEIIYWPkg08IIYQQQgghhBDCxjhXS5dtCmp2A5NAccOlLoealSBW5MyUilYsPxU7\nz0iSb5I22/zq2rVrS5qb2pmsnhJ329jRJGMsz8guY5toWX1Rgs602Uxo6WId2KaXFZvWqM2Y5NPk\nfmv1ctE4q412R3Vhls3KNc0CVpGNVqSd5yXvrlCxYNm4afmMfmfn2jhoMnmrO7vWrVTXFxW2b47r\n9hzXxkCOqRVrrM2JLBfnGG52bBu2m3XJ2n23SzE/XpM2K7NW8z64nmAgAc49ZqnmBtGVzdBHgRps\nLVLZ9NVs2TZO2AbwZq8ZpW1OtM0vt2zpsrHxvO5ndtPdWdsfsXl8tGmz2U1tM9xRHzl5DvuUWS8r\nGx+ftb3ZxlC7JyuX9fGK1avnb+P9WbWTLWDzjdlpRmtNqzfbeJlU5lDL0yzdNleO2kDlXa9SFlJZ\nj9vxyjv0qL7tfdP6oz33Q6xT1g5G7aoyV/Cd2CxolesbF/PtNIQQQgghhBBCCCEo+eATQgghhBBC\nCCGEsDHOVbdnEkNKHxndgsdHEaJ4jkm6KlKsiiyKUjaTKJscm4wkl1YXlLAyP0q377777uFxYpER\nLDIX69rK0Ou1IvHj8yAmO2fEFZOPm3XH2tio3ityQ96z7cjONsv6ukgcIuFlvYyeF+ve+rFRsQ1Z\n/6lIVNeOV2yas/L9ynhTkZlavc/I1O131h4simCFSrl6eWzMmolStkVYFxwnWRe0H5nlpudj0bLM\n8mT9gdehverSpUtL2uTK1k95Pueq/luL+mXWMbsm29Tly5eXNMdyXovn8LqEZeD8MLITV6LmEBsb\nzB5g8vVZa3rPp2IrHf3u5DW3YPHk8z9krlir/0pEPFv7zKyJboTZokaWLvYd1hH7AscV5mG2f6tr\nXsvGu4rVa4aKLcbKYte3tYsx6u+ViIfkdrd02XvEWjSsyvuHPcPZ91NjdlwdtdnK9Stt3fK0eqps\n57BWB5UyErOLk0O2aDEL51q9W0RUG+crNkAt79TZIYQQQgghhBBCCOGWJx98QgghhBBCCCGEEDbG\nuer2KGUzydxrr722pC1iFeVNPU+TsM7uuk0OkU5Vrru2e7dZNqyMlLxSkm/52z1Rdst8RtHEbNf4\nyq7iJjVnlBXaEwgj1FSk7CP5ut2/RVthvbCMhOdcJGZ3eydrcspZ681sFK2K/LliAbNoeZ2RNeNG\nVCI5VLDoKGTUlitRvGbrzvpshcq11sZZi0xxu2ARD/ks7rnnnuH5o+gdlWgcsxYePiOzjFkbtP4+\nivpjZbcIQcTk2rSjce6x9crI5tyaP6dRdEvrU7Njn0nmK+shs5aM5muuCSzCyEzEm5PnXyS4pq3U\n82nXB2a/Y52z3XN9YmU066NhNqpR2+G/2xqK17etDGj7ssh3I7unleskZz2HHGLpqpSXjNbe9j5g\nW15UxtuLCu/Txmli1uLRVh1msTSr8Oy7ZKW8hPdqc/fonc3SlejLVl6zkFZs3Dx/1Gcq0b1mtg5o\nzfuajYlmqa68T65dx9qPjfOJ0hVCCCGEEEIIIYRwm5MPPiGEEEIIIYQQQggb4w2zdBGTgxkj6Srz\nrkS4seOz0uKZHdGNSjQhi27E31L+Suks68uioPG6FvVgJL0zOb7JCgllahaRjdYttg1GqOE5xJ5N\nv5a1NbZH1hePm2XudreZkF7/h0SCsuhxpNLXKtGdZvp+5Tkfcp2KpJus2QlMLl6RkTM/ixZgZbEy\n2LMf1atJjU0KTC6qVcQwKxDTtCKtyfcrc2VljqucU4koZaxFIZmN3mbzk1nQCMchXrcSfWXtGdh8\nanZTi5xUicBkdbBmha5EODGsnVzUfmrRXs3CwzZiUZlG7dfagkVDZTvm+ohpi9JqVKLp9rWj2fvN\njmBbB1gEpIo1zuwRpGJXmaFi3TIqZbRxcBTxtxKRzZ77FixdhzBjlbFxd2ShPon1a3vvmY0ctWZv\nrtiQbL5j3nxntPZl88bM/GTzlFnsDI4fh2zdUqHnbxY0m8NJZUysEIVPCCGEEEIIIYQQwsbIB58Q\nQgghhBBCCCGEjXGuuj2TdJmMyeSJlKz3tMneZuVas5FnDqGXx2RZlM+9/vrrS5ryObM7mP2Fxylr\nYz60hjHPu+66a0n3MpvE0PLjvZrFj79ltAmLTkH5Y0VW35+xlZ1tgGWv3OtFlaYfgt1zl4xXoukQ\ns4EcIm1ds4TcqDwds17a8z+kLZx1FDCzcZlU1Oq3Ik0261ZFPtz7r0W4MHsguRmy3FuFWdvMWhus\ntNFDokjNXve0eU5Lm6UeK2O5ydTt/JkIepXoXWt536gsld9aRKiep9nnK1Ts6xeJ2XZ3yHYDM2Wx\nuc+Oz96HzQ8ju3wlPWthJrynQ6zQp6Vi3TFmozGt9dm1vnvyuJV3y2vaythvx0fRLe13d95555K2\n7SDMUm9bSZj9mNfiOaNr2TrP1si2zrLjFWtiZS042kqgEunT3n1J5fqV6KSV/jY6tzJmjKKRn8y7\n8h5ELv6MG0IIIYQQQgghhBCuIx98QgghhBBCCCGEEDbGuVq61nb2PwmjCFDSNLIWWdSkijx2NtrI\nzZQ4UqL1hS98YUm/8MILS/q1115b0qy7K1euLGnWl0XjMOkd86dscCQ9q8hQLRoYrVgWvYltgM+Y\n55vEfE02V5Ek2g71zI9lvF2idFWiwIyw3f+J5WdycGuj1jZNHjk636JfVSxih1gWKjvxr0lImQfb\nrtkUOT5bO7b6svHR5MhkLcKSRSWyeWPLVOYek06P2kvFkmTS5sqceLMjYKxd37BxYjbCV4W1PCvR\nuKyuba1jc1jlXm3MG0VdPGQtdF5rqpvJ7DYBp40maNsb2PVtncffch6ozInMx9J97LEoNGZhMctx\nxfJi+ZBDLGNrmE1xNkqY9UfLf2S7mR2fjS30TWLR4SqsWbqsP3I7Cr6/vfzyy0uafZDp559/fkl/\n8YtfXNLsp5cvX17S73//+5c029Tjjz++pPv7JNdNfNezyGCE794WwdmidFWs/mzrd9xxx5eludbn\nvMb7eOWVV4ZltyjPhOOKbX9C+Iz5bGycHZ3Leq9sc0G41UuFKHxCCCGEEEIIIYQQNsa5Knzsi5n9\nxZlfvvgVkJs2j/K2r2SVv8xVNlM8q832ennsrxj8amlpU7Sw7qgUsr802F8j7C8/HX5xtTyY5vl8\nTvZXJZ7DL908p7Jx1eivIaYAsrKzjfE+7BlcJNY2LL7RObaZcq8v+8tc5TpUT/GrPNNs6xwb+Fs+\nLx43pdDomP1F46z+AlYZe6xso7Y8Ox7ZxoLENhO04/xrkm08z3TPh33dVHbMz/5SOrup3a1Opa3Z\nX3ln2oONaZXNKs8K+ytzP27/PtsfLdiBba5p9WF/FR1tjMkxaHbz+rW/8rd2/Zrq1VdfHZbFlCcc\nT0fXtTHW1GKV9EXF7t/GHVMyr41ZVlem5K4oSkzlZv2aedq1+lhuCn6O66Nx/0bnWHpWHUROq1on\nlWA01h44xtiYW1Hb9vswJRjbiSkwSGU9eKtTUSJW1NOj9lAZs/ne9dxzzy3pxx57bElzbGYfeOml\nl5Y02zqvyzZNRRDz4bV6nrzmiy++uKQrmwc/+OCDS7qyLrDAPBb4gIqZe++9d0n3+YxzE+c41tez\nzz67ek1bO7OurW9a8CDOBaP32bVvGK1dX1+j95GTTKvVps4OIYQQQgghhBBCCLc8+eATQgghhBBC\nCCGEsDHOVbdHqRUlTSYxpKTJJIkjqR6lbnfeeeeSNtkor0PJmEmqzL5glqo1W4jJslh2WlgoZeP9\nU9bG61vdmeTUZN8j6R2vQ4uF2c5Ydkrm7JmaxY2wfvlb2xS6l8Fserwmz2Gb5XHet0n1bnUqEl62\no4rsudezbUxnMmvKOq1vcvM4prlxOZ8F82S/Yp5Md0z2XpELz1qqZi1da3Jk+3fep1kpza7F58cx\nlPJlHmefpZSYYxV/29NmTzGLGNNmxZl9HrciFRuMPdM1O03FtnyzMSvDmnR51urGvNlerH3zeMXS\nZfaePg5dunRpOcbNKStltzT7GjcJpZ2AfZB1xvGRa43R5vH33Xffcoz3QWxTzlkJ+q2OWRMq82nF\n9jWisgl05Tq2zjE49pr9t6d57GZbusy6VVnTjjgrq+qs1X92Y+nR1geVzbJvF0sXsfq3dZxtjL8G\n2z3H4GeeeWZJ02bFc9jubeNhe6/j+VwL0erV09w0+sknn7RbWWBd2Hsd0/aeYFYo/pbzCeuyz5G8\nf9YXrWmsa44r9qwrG8lX3gMsyFS/V94z30GY5rsM2yzn5EO2k4jCJ4QQQgghhBBCCGFj5INPCCGE\nEEIIIYQQwsZ4w6J0MW3RuCiLsl3/R1LGSjQhyqh5HbP2WHQYs/ywPCZx67+1SAtmSaEFwuTolN5Z\n/iYHq8jEeh2b/NXk7SalM9uGyaTtGVtdj+SylbKbTG8UIaG163eWv0hUpPZWX2vtpSLp53G2e0oc\n77777iVN6xaPX716dUnfc889w3wooeS1KJvs5TFJqlkjD4kEaMet3tfaL/sIy2uWLmKWLspoKUfm\neEN5MdOU3Vokvl4HHAMs0oNF0LMILuHLsUhXxMZpi9oza32slMci681gcyXnU7Mgcs6vtCmbty5f\nvtxau17ePRp3WnNrHuuI5aJ16+mnnx6mKfFnnhwfR9ZWltmi/1Qij20N3jOptPU1Sxefj80rlbmh\nEvGpYu+36IujtTn/3WySNyNKVyWS2FrkxrOys9ozmI10WIkIdVoqdr+LitW5ncMx2dYnHWtzTJvl\niOump556anjc3t/4fmH9hMeZ7vMZLV0sl41lbCOso0rER1KJBMn64/l9fOBcyXmb1jRuHcNzDLaB\nSlRTztG2XcooQjDvua8DWrv+ncXecS3icKJ0hRBCCCGEEEIIIdzm5INPCCGEEEIIIYQQwsY4V92t\nWWII5VWUo1nklZG1yHYAN4k4oTRuFpNH8rjJtDuUcVG+xt3LKVOjRJv3SqkeJWNWLpaF0jPW06iO\nTQ5XsY5VoqMwT4t8Ztey3cwrtpsOnwfzYFumPfCiRukyyWvFrmTSx952zCJgEdVYn5Sw0sZFuxbT\nPId9hrYv5m/pNUsXOcTSVZGQjiLlnCzP2rhCzOJp0Qps3LbxwyS67Ne0qPKcPg7w380ewPGDWH1t\nIUpXBYs2MorCVWl/tFtwXqHlic+Qc4bZlay8JrEfjRUVOwTzo/2JsnZGjONx3p9FBWLdmA2C40q/\nD45HZj2wPs2y8Hkw+gttXDyH92rrJNoJeE/9WdISa9Z4UrENXlRsHWnY+Mm+sWY5svzsuNm1SCUy\nq9m72Ad62uxaFYuW2UbN9m+Wmko/HdXHzPrwJGYFsrWjbQ1gfcnWI/1aZuOetX7MtMGLQMUeafU/\n+q21XbMm0tpuERQ5TrOtc4y1NRrnKqY5n/U0y2W2R7Nccf4g/K3NYaxfs8/ZO0Ff69F6zLLQxvX4\n448vadsexKyftr2LWbQr99GP8zmyndg2Nrx/mytsnDCi8AkhhBBCCCGEEELYGPngE0IIIYQQQggh\nhLAxztXSRRmTycct8ortAt7Pr1gvKMsy69Za5ISTZTTLAM8xaVj/rUX0Mgsa7Q6UClIGSGh5MYku\npfcWQYR2pVF0NLNSEJO8mlyY+Zg9wCS9rLORragSSc3OsXKZfekiUYnqQey593bK9sr6YXsyS5dF\n6eI53PGe59hvWR6mR+2L9zOKJnWjtPWNStrq3STbI+ms2S05Tozk+K35OExbTEVWb3YOi+TUxx4b\n72zcNpntFqKNkFlb2llYaNguKEenbYhtzWySFfkz+4xFSOzH7d6sH5mli/fE4zyffYB5mhXZLDXd\nZlqxTNj92fN44oknlvQzzzyzpE1uzzGXfdCs1h2z2pO1Nc9WMEuX9dObaZWp1K3NGTauzo6f/b4r\nkb4sPbuOrkRMYjs2W8wo7wpmW7F1LO/DbJWViJ2jtYCNq7cjvH9rx9YfbK3X2xH7i80ZZg82C7FF\nX7btK1gGWprY1nmtnj+vyfdHmw/MfsQ6rVibzYpklmZuydD7EvsU5z7eJ++Jx/l8bT6vWKTs+4K1\nmZ4nrdL8d9u6hc93NrKfEYVPCCGEEEIIIYQQwsbIB58QQgghhBBCCCGEjXGuli7KXy16CLEoMCMs\nSsys3JJlZJp58jjlYGbnYdkoh+7HLUpJxdLGa9qO5MRkjsyHUTgoJxxZpHg/Fbkyy8X8zDrD4xbB\nxSwntAxRqteP2+7oJmk3SwLri5K8rWFWL5OS9+fL58CoWzzOOqSFx84xa5jZtdimKpEsRpauWSp2\nrVn5uMlfmX8/znbMvs5xgv3XoqAwH0p37Xwet4grVge97Gb5ovzVZO9m99wCZ2XpGuVj85BJxBlh\nhOOn2esqkeTMbjiyFpuE2u6DbZQSe0rpzdpSkaNz7plp3xXrBe/P7AR8HpS1c9xkxE5avQnrYzTO\nr0U5Olne0djUmtvetmBFsXszKnU6cx1b91rdmo3d+pLNZyNL13lGR7Q5hqxFw5wtr0WAqkSts/eQ\nmbq2MtsYW1nTbKEPsv7NPlh592S6r5cs6haP0/JMyxWjcfF8sxDzPjg283zOm7QOcX3X5zyzP1nf\nYTvi9glm47JIqhali7BsfJfq8z/nbUaopoWZ8yDPt35aiepq24/YPM/f9vmXdcT7t21Z7P3/EKLw\nCSGEEEIIIYQQQtgY+eATQgghhBBCCCGEsDHO1dL1yCOPLOnKbvoWdWpERXLNdCVSDyOMUNJFKRuh\n1MvkbsynQ1khJXu8f7PQ0M5iETNM2mqWJtplTHrXy2kRD3hPZr8yKZ3Z/SxCAeE5Zgfq0Zv4rHkd\nSiVHFryT5WU7YVvaArYrf4Vep2ahMvsk25/ZQCuy5Erkj7Wd8K1dVuxaszL9itSbWNl62U2WzHHF\nom6xn5pdi2NcJWLXTLoSsYRUxoNQx9qLzUkW/YljsLVjXovtzqy6vd2ZZcJk+hZVhNfhfVjkSl6X\n9cHjnDdG45zNq7P2H5P1sw4ow3/HO96xpO+7774lzTqgFWFkE7L6ZR80KxA5T6vPeWNzZSVKVf9t\nxe5bmQcr9Ww2hVlbcj/H2siahfrkbyvpQxjZf2fnjMozMPt1ZZ6ztf/ouD27Ldsnjcp8Y7AeOVf0\n39J6xPGS9pzPfe5zS/qxxx5b0vwt5wmzVHFs5vshrVucc9esxRbxydo9877//vuHx1kuSxN7JyCs\ny/4M2HZZj7R30WJn9j27vtmPbXy0LQ5GkTE559v6g2lbFx0yb2Y1HEIIIYQQQgghhLAx8sEnhBBC\nCCGEEEIIYWOcq6XrPe95z5Km1MtsQWaJGEma+e9mv6IsijYck7KZ1KoSEcRsaiMJZcWyQfkcr08L\nEXc1532zXCYj5m7mLDvraRQphGWklNDKzjQliRYJiPmYvYjP+8qVK0v6gQceWNKMTtLrzO7NymWy\nPosAdVGZjTBi9PqyfkwbEOWO9szNQmJR8IhFh6NtY9TuKtF0Kv3L5LomJ521dI2Om3TZotCxjIdY\nuth/mK5EAevHbey1/miwP24tYtch9LZWsQvwubHO2XdomWX0J47HbN/WBgmPj6LJcS4x66+NHzaf\n857uvvvuJc25gtdlGWlfY6SQkd2N9q9Zu4XNQ3x+fB6cBx9++OElTUuXPePRcVsvWb3fjtYts2PZ\n/HBerEWoau36e5q11m75WRsWTdjahs3bPP+Q6KCd28W6ZVj/qljzbT7p6xOL0kVr0ZNPPjk8zjWR\nbWthFkd7T7J7Zdn7GptzGdscrb+jLTBaa+2hhx5a0nz3ZH2YXcre0S3q9OhdqrJtCrGtXiyCLzFL\nl20VYVu99LnAnpG9J1iUXdu6pUIUPiGEEEIIIYQQQggbIx98QgghhBBCCCGEEDbGufpP3vrWty5p\n2n9Mdm+SJsqMu5SMkjLu3k1pLaVxlFybDNWkdGYbofTNZLGUb3VrCeVltLZQVmfStEp0hZdffnlY\nLh7n/dEaxnxGUVFMSsdnZBYaHrcdyWn9YFlYT6y/e++9d0nTTjCydFGCT3jcrDgW8cUix9zO2E72\nlSgKTPOZm/XTJJZsR3xGFn1nxtJlEs+ZqCYnj5+FpYuYtYX1Yu2bY/UoWlJr11tCzd41suWcTPff\nMg8bA6wew5c4bb1ULB7sO5SJUxpOW5RZ80w+b/NA7xuVe6vYMLn+4H1wzuA9cd4ymzjLxnbfr3WI\nZcOiRZrF7sEHH1zSnBM5b3Ls4zqG99TvwyxdleiaW2PWllVps6OIS6N/P4lZgswyQCpW5IpFeVQf\nleiMFatG5bc2h1Xu40bHbkQl6tFo3X8SjkOV6EKjc+xdytpMxep1Ue1gVoeH5NPnIY7pFQu7bevB\ntmB9ljYne7+grcys871vsI8wb1qxOQdY1FzO/zbGj9bUrV3fTm27Bc65vS2zTfNcizLN45wf+Y5X\niWLNtG05wmuxHay1vcqWEPZ+PPu+ud2ZOIQQQgghhBBCCOE2JR98QgghhBBCCCGEEDbGuVq6aBUy\nmZhJySlNo32gS63MgkDpGPNmHhaxw6KKUK5lFrSZaBv897Vdyk+eQ0zqTdkX5X4srz0Pk83152HW\nE5PZMj/WHa9vv2WacnTKD1kHJufr1+I1TQrMPFhfvFdKGy9qlK6K1NxsQUavL9Yn+w6pROpjPZvl\nh8+Ibc0ixVm0gP58zZpgEcMqlqNKpBTL36LTkV52i/pgtjeTkFYsXXYOpc88bnLnnrZoXBULq8mL\nzyLyyRtNRZpeiTwyg83J1kbXbJIn0xZ1wiKSjPKojEfWjlh2s6YxbdflcUrsR7L62ediYwavyTmR\n1i3anM1OwjLw+fH83pdtTq48g0NseLciNyPyX7//Q8arSkQYYhZ1G4fX7FIVa8IhVrNKumKVGLXZ\nSju28+19g5jVaLbsF3WteV5wHCO2VrA5ieuTvn5llGluD/L0008v6RdffHFJ2zrIIkfZGsb6DMvD\n8nIe6v3atsNgWWjFtrnE5na2XdYBt13hnGjvjaRfy8YJrumZ9yiP1q63r9nczrLwvYXfDiqW8f4s\nLRqZvY/wndWiGM+OVVH4hBBCCCGEEEIIIWyMfPAJIYQQQgghhBBC2BjnqgmkTI1S4VmryMi2Y7tu\nm+WK51t0CZN3MR/K8yirM0kmr9vldJSa8d8r8lCT/pn9ySIg2H2b1LunKW8zixTz4L1SPk/ZIOV2\ndn3aAyl9Y+QxPhs+s16vlQhF9hx5nPd0UWW2FmnKqERe6XVkETgqEXnM0sW0SdDN0mX5jOS9tlO/\nyYIrdXdWEaXWonSZhYZUIq9YdCWLBsHjfDYWpYu/7eePLDwn2YJFa5ZD7C4VW+EaNk4SK6PNMZVI\neGTUvm3dYDZJYuuSSnQUm58sms7I5mr5ESu72ZY5t/L4rFVkrY55rBKt0tYFF8nGRcyCUJkfz2Ie\nsGdokWFnLV0W3WrNclu5JrkZz9+uuxZVbDbyGqncR8UGaOfY8Zm50MZhO+eiYpYjwrHOoqqNIkTz\nPYO2KVq6nn/++SXNNQ7XQZxvLDqi2bVG7zStXf/sRu+ktGUR9gtaut7//vcPjz/zzDPDNCNEfu5z\nnxuWnWnOTxYNq8/FNh7ZnEV4nO+bvD8+A1r1Hn300SXNeuJ9rM0FvE++v7K+RluPtOaRvM0Ob0Th\nE0IIIYQQQgghhLAx8sEnhBBCCCGEEEIIYWOcq//E7C4V+anJpbokjlYoyr4sb0rTTLpt9ipidhXK\n9mxH8tEx5mERgixtUXB4r8SiCxCzRfVy8v4pO2PZTeptO4/b7uR8TlevXh3+9u/8nb8zLC/p9z0b\nbeSQCEy3Ojez3GyLBtufScotYhyfs0VYY9ryGdlMzHoya/UyiX9F+m+cNkoXqYy3fB5Mm43LLHln\n3WdmLV1bsICdlaVrNrrDGhV7Do8f8vxH+ds17To291X6LKlYgZnufYP9qBKxy56XReM0S1VFBm/2\ngFGEsdG9tXb9HD7Ko7X5ur4VsedySP8a9YdK1C1ri2aDIHaOzcUWQXdk457FthQwZqNxrUV65Hpi\ntl1WyntIW7f1SL8n9nv+e6WvWxm31jeJzQ92/73u+F4y2qajtev7hc199o5nZbHnaFsccK07ipBr\nkaP4O+ZNyxMjcPG3tKPx3ZP2MvZBzhWsP9qeRtElueasrO0YjevatWtL+r777lvS9h3B3kmJRRUd\nRYXmfVrelQins1zMnhxCCCGEEEIIIYQQlHzwCSGEEEIIIYQQQtgY52rpMimlydrMUjXaGZsSrYce\nemhJc/fwz3/+80v6537u55b0I488Mvwtd8+mBIt2LZNRm9SZFql+T5TaUfZGiZjJ2ygd4zmE9WuR\nHCxt8t5erx/72MeWY88+++zwd7wnytr4fFkHfL4f/OAHlzSfMZ8Nz3/44YeXNJ8Z6bI5k01SYkdZ\nn+3iz+d+UaMbHGLpMjtHTzNvs3exnk1mbOdYRCmzD1pUtVHErjVp743Ka+ezjuy3a3atk4za3axt\nxmT4FVvMWdHrzJ7vbLTCcDg2f1ikHqPy7NjHOc9y3uB8OiqjYZGIzH5l8yCvZZzfQQgAACAASURB\nVHlaNJV+/qzdgFQsLBZZj2uHivVuNP+zb1Ysm2dl5QtH8HlWtkMwWxaxtbnZpbf47EZbAFQiallk\nIbN+HMLMnFvp38Zs5MRbkbOyVY7Wa5yP+C7CCFjMg+PuK6+8MjzH1nZ8FrbFBfPn/DiyKNm7i0V2\nJBULK+cH2qhsOwCzOrFe+zPgvDqzjm/t+nuijevBBx9c0vauwrKwvGaxJL1eaW9jXZu9y+7PLH4V\nskoOIYQQQgghhBBC2Bj54BNCCCGEEEIIIYSwMc7V0kUZF6VTlGCZPYSSNaZ7Pszj1VdfXdKf+tSn\nlvRHPvKRJU370eOPP76kuQv5lStXhmWk1JxlNNsGy8v8uzSL5/7Mz/zMkqYd7YEHHljSFkXjXe96\n15J+29vetqQpH6NstSLdtShgfYf2F154YTn25JNPtjUojSPMmxYw1jsta5S+sT7uueee4bVGu7wT\nPjuzJ5gVZwvRf2blryZfHFkfTLZq0dusXGaZZP5m6aI80ySfo6hx/HfbNd8iY9jO+maZsH5dsXeN\nnkelXZo03yT+FXuV2TYqEc9GEcasfq2MW+iPRqWfnkWkGLNZc26wKIiVSFP2fDm3cv7jb/v8wLLY\nM7exgRZiltfWKGu21ZNltIgdHav/itWd55iNzKJr2jhkVs2RZc3GL+unpHL9i2QhYf3MlnvNHsG6\nMvukWboqVqRKuSrz7Kg9VqI/WnktYpitUa28py2D1alh8zP75lrku5Pw2dt6fPRs7P5t24FDbF8X\nicq8aX15tAakVYrvdGa3HG3l0VptDWxrSr7TsDwWObnfn0Xg4nsi351YXr6b0ZrGtM3LrCezZvEc\nlr3fk/UdztujCFkn4b2a7YxrEZ5fiWZG+nsr7X68T9a1Xce2jpm11kbhE0IIIYQQQgghhLAx8sEn\nhBBCCCGEEEIIYWOcq6XLZMMmnyMWvavLqCjR/nt/7+8t6Z/4iZ9Y0k899dQwv5/+6Z9e0ozS9e53\nv3tJW1Qekygbo+gztKB9+MMfXtKPPfbYkn7ve9+7pHn/TPP6tD9RSjaL7TQ/kh+a3JRlpHzOrDWs\nI8raaOOi3I/nX716dfhbln0k/7c2aGmTiG5NCnsII4m0jQEmz7R+ZxG4KBU1OefIunUyz37cpJRr\nvzuZ5jVtx/1DokqYtXREJfqPydpnbVwVyenofLsfy2/LNi5y1tH0ZvMzy8AhZaEEnPP4Sy+9tKTZ\nZ/o5ZhGzMZjl5ThhVixSWZewLs2W0stpNpCKjawSAZRpk9hXLF0jy4vds1m6mN/WoumdlaVr9Hwr\nNiQri9mlZn9r88BaGzGLFi0TlbRZ2SoWsIq9a/Rb68dGxU5s/dcsyhYVcG39NLuGuB3Xqxx7R2Nz\na27l7+8gjLhka06+c5ili1Yoazs2fvNao61CWrt+i4t+HywX8+C7Gd8f2aZos3766aeXNOdqYuth\niwJGSxPf5fqc//LLLy/H7H2U92/vfbaut+iWFqHQbJOs195WWL98J2db4rtyZQuE6a04ps4OIYQQ\nQgghhBBCCLc8+eATQgghhBBCCCGEsDHO1dI1sjO15tJlk5uPIutQXvaJT3xiSVNqdu3atSVNudbP\n/uzPLmnavmxnfZOpmdTZ6LI2luWTn/zksCyUfdlu4KzTRx55ZElTXlaRlprMlDaqLhVkHVE+x/JS\nvkfJHqWQhJJei+ZmVh9KGNeiGFm7q8jn7JzbBbNjjerCpNU8l8/c6tOslGYNZPuqWLBG+Zh1zI7b\ndUz6aZjU2iK3zFiaKnL/ynFLm6WLz9jO7/VuefD5zsrRtyBfr9xDpe5G/07M1mHjPdtfZWxg22Wk\nR1q6zL7Qj89aB0nFqlKhsl4ZrRdm27FdZzYC0iF9pqctaozZ1LaMWW8qrEXpsmMVy9WsHczOsYht\nVp6RtWjN/tWaW7cqtqw3GrPcWBntvcLytKh4ozR/Z+8Js+PNFliLCtpaLXrayNJFaIVi9CWzPBHr\nA7buZdqiavGdl3Nrh2tR2w6Dkblo6eJx3h9/y7TZf3nfvI+v//qvX9I9KjTPpU3O3t/MAse1C3/L\nPLnVCo8zehfrdG0bE4vMZducVLYymH33vP3eVEMIIYQQQgghhBA2zrn+Sabyxdn+msgve/xLcf9S\n2L8Atna92oebI33wgx9c0vzrP//C+Nxzzw2vaSoC+0udKUNGf/HkV3l+NWWaGzjz6y8VM7wm68A2\nn7Kv2Pz6yd+OvvrzqyW/VN5///1Lml9zeU+sU9tQ0/4KZF8/+RWX9zdqM6a0sK+m9teu21HhY6z9\nhXx2Q0Ri59tfw2Y2Z25t3L54Lq9jx9kWqIgjlY0abRNzy4eMzrfnYioK63c2ljGfysZ3drz3UyuX\nlZ1s7a+TZFbhUzk+c03ON4Rt3eZz9jVuNmxzrs0tthn7WtlNjWJ/Eaxg7bTSf0ccouCqnFNpA7aO\n6WOeKR233O8qzPYvm89G+VRUNzzH1JQ2x1TUYTZmj863689uDl0JGGB5njZtc1wF1pHNzxV1km0k\nbwqPvmavvJswbWPTltV6rH+OZRX3Qz+fSh6OgXx3obOBcxbPoVqEKpKRGufktWzTZqpLRmsrXp/3\nxndl1gvfj/n+ZgEODFuD28bRTPffUklElZUpxgmvY5sj8xlwQ21+X3j++eeHacL1UL8u24ytZ+wb\nyej99TTkTTWEEEIIIYQQQghhY+SDTwghhBBCCCGEEMLGOFfdnm2UVJG2rklRn3322eUY09/yLd+y\npL/zO79zmN9HPvKRJU2JFmVUtsm0ydRM7kbJVt+4iRs4vfOd71zSlIBR9sXNpFgXLDstXba5Juud\nEkKzcFCi2DdHfvDBB4fXede73jXMg+Uy6SzLyGuavNY2zbNntraBc8UqsmXJ61lj9kar89NaT07m\nb9Jpk1qPjh8inzRMXm1t1NqdWVRGthTLo2KrO6vnVNkIuj+/ivXU2lL65jqjjY8N29jRNuk3mbzN\n+ZzPeA4l5g888MCS7vL1yob6xObtyiaeRmWuGOU/a3+yfmdzaMUGWSn7yELC/mXWOLvm1mxfs5af\nCr2+KhsWVzbUt3PIrP1pbdPmyu9uRt3dStia1sYqs7ubzeOssXlz1uZ6q2Dvj7YdRMWS2+c8HuM7\nCt+dOD/atha0KFXWYiz7aGPgk4zmYl6f77jMg3VB21llCwJiQSNYN7Q/sbwjeyTrmu/NZunic+Iz\nYN2xXLR0mY2L3xf4/Jgn76O/u/Pfec9ra/fWrq8L2uFn30+i8AkhhBBCCCGEEELYGPngE0IIIYQQ\nQgghhLAx3rAoXSYftIhVJqHrViTKzpim5IpSr/vuu29Jv+Md71jSjIb1zDPPLGnKyykBG+0k3tr1\nsi+WfWRDoCzr27/929sI3gfLaPXIXdttx//Kzub2zLo87T3vec/wdw899NCSZr1QhsdycUd0i9TC\n527Se4tiMLoPkyGatNLk6CZZ3jIztig+h0qEClKxA5hthKxFyrPjJoev3H+lvMQsWib5pCx2JDu2\nujbJq41TFu2O588+V8t/FCnF8q70R7IFq1dlfKnYU0f/budSfsw2x4hdJss2iTLbEaOG8BnRJsao\nj93qbH23gpXLrF7GaaNkzdohK7ZKq4OzslH1+rA6mo1WeYh191ZhdtwjZ7FWmLV6WXktGlclklZl\nrH4jmLU1js4/5Bmx383a2mbH+fDlWNQti9Jq70M8ZxR51aKVmqWLViHafGhtJlYWzrNmJ+J7a59b\nX3755eUY03w3Y+RMvpvR8mRbnhAbP1he1hPP4bqgP0uW8cqVK0ua9cv3RM5J3BaF5/Ce+Az4zs36\nMEsc65rfF/q11t5HW/Mx3MaS2Tk0Cp8QQgghhBBCCCGEjZEPPiGEEEIIIYQQQggb41w17hUJou1s\nb7/tkiZK7ZgHpVif/OQnlzTlYI888siS/vEf//ElTakX5WAmsRvtKn4SSsm6lI1l/47v+I4lTVnY\n448/vqRpFyNPPfXUkuY9VWwmpCLN7tI6Rk+hNI/RuyzSF6/zwgsvLGnK6ljvFRvNbOSWtfwO2Yn+\ndqdLFS2SXYWK/HnW2sFzzKbVj1vbYl/nPVnbudl2IpPbj7DnUYkYVrEEWOQes6zN9JmKfa9i17mo\nzFomrL56HzB7A9sFZdR8VhzL+TztuVD+zDF+JN1u7Xo7L+frPl/OWNdOlt3Ss+2yct3RGFb53ez9\nkUOsVmtU+mCFSpTOW52zsvzMYH3WLCkWvcui5s1GSLSy3Uxm664SNWxk5a9Ywe18s0gTqy/Lfy26\nYKXfn9W4dpGojP2VaLK9nm3rCIP58X2P82yljdo7sVmXuOVIn8cZKZnX53zLd1/2C26XwvmcWNvh\n+Yw0RVh22r76vbIstFDxXFrQeD7fSdk3adHifdPuxvUKy262OlrQOxa529qPWXFZxkTpCiGEEEII\nIYQQQrjNyQefEEIIIYQQQgghhI1xrpYuk8FRjmZysB6Nq7XrJVX9OOXltBlRcsWoW7zOe9/73iXN\nfCh9s4g4ZpficZaBcr5eByO5emvXy/F4zbe+9a3D+/ipn/qpJc0IKodIwwnrvUvMTIJnkcF4H7xX\nnrMmWz2ZT8WiQ2aidFmEJHJWEveLyto9898r1g+To1fk85XIc3bOqA1aVDtKKWftWibL5Thh7Zi/\nZX/k8X5PFr2OWPuuWLrMsmb91MZ/O38NG3stD9bvRcXsHDYGrY1NJl1nHXIuITzHysL8KYvmXMy5\nnc+Ucy5tZf26h0QEsj5VidJVsWFY9J+etno/bdSvG5WlYumezX8GuybHVqb53MPpqETXskhes7bo\nEZW51ywLleOc+yziH4/bdS0ia6diaXujbPyjflVZf85G+buo9i4b98wuZVszjOrF+hTnD86bFomS\n8xotSjzfoqTaenS0bQjPZ3lpZ/rMZz6zpD/3uc8taUaF5lxta0SWnfXEPmuWMVuDXLt2rbV2fURt\n5mFWM+bHd1XatR599NEl/dnPfnZJczsYwnxY73yP57t7316F7+38d1tfsy1ZFLbZ980ofEIIIYQQ\nQgghhBA2Rj74hBBCCCGEEEIIIWyMN8zSZbYoytfMMkD5bz+fEa2+7du+bUlT0kbJHKVsd99995Lm\nTuWMekXZGSVzlKmx7JRdUQJG+n1cunRpeB2mKQ9kfVEmb789a4l2a196lqwv1rVJhy0qEGWAI+vY\nyd+yPZgFy+Sq/bojG8zJPCpRD/isD4na8UYy2y7sPtciFpxVNJZK+za5diU6TE/z2bKN0o5IODYY\nFQm42SOJSXp7OXmM92HHzV5WseGxjOy/LCPrbC0KiclyiR03S9cWrCKV6B2V6JajPMwCyPZi1q1K\nZA5GYqRcmnOxtRGbN0ZULLYmR5+NvmJ5ErMNnAU3w9Jla7CePqt7MIvOReIQC7f9dlTP1u953Owe\nleg4s5Yus1P242bLqljK7LileX+zv12zd61Zvk5illCze1q6MiaNxjBrUxV7qtlJDrHOvpHYuGfr\nP5sTRr+13/HdlHYtwrmM1h7WM61TtCsxf2sv9l7VLVCMYvXEE08s6R/7sR9b0rR3sX/Zlhy8Js9n\n2Tn28DjvlWsB5nPPPfe01lp797vfvRxjfXE9wXUe17EvvvjikuZ98z2fxy1KN9/FWQZ+R2DdfMM3\nfENr7fooYXxeFiWM7YTvA2xXs30zCp8QQgghhBBCCCGEjZEPPiGEEEIIIYQQQggb45aI0lWJJkOr\nBM/pErf7779/OfaBD3xgSVNm9a53vWtJU0ZFeRWvQwmYSU4pmbOyU5o1kojy+rRIEcrhbMd55lOJ\nJHYIXTZn16Q0zXaoN+sH05QwWpSdNbtfa+vRV0zOSaweK7+9Hen1z+fJ5zAbdWtWXm1UpLsjKs/f\nrjPLbIQxs9p02EeYplS1YoXiWFaJrsg8R7az1q7v131MsPGWrEXhq55/keD4xjHWImmdNZW2zjK+\n9NJLS5pRL2nv4jxA6bK1tZlyzUa0mrHDnTynYqMa5TlrkapYfcxyMJv/KG0RoAy7Pvs4x4OLxCF2\nlzVLV8XGZWmzd1Wid1VY64/WhuwdwM6xeYtjg9WTrU3X1h2VdUZl7VJp9yyjrXVPG0mrYh2z/LYw\nVxr2XmB9bNRO7XesN/ZB2zKiAvO0CFFmP1p7N7GymwXO2gXLYhY01gdtXKwPHh+9Q3ILE+s7VnZe\nn+ebddy2ALDIX/wtLV29LfH6lf5l92FjfoXt9uoQQgghhBBCCCGE25R88AkhhBBCCCGEEELYGOdq\n6TLpdEW2SUnTyCJCK9RDDz20pCkRp0SLEmLbgfvRRx9d0pSSXb16dUmbLNYkpCMbhMlcKY1jHryP\nZ555ZnhPtLiZRNWkhbyPtWgmlOPTJmcWNMraeB+0z/GZ8VkyT/6W98drWfvpZTc5ukmNTSbPezok\n8tQbyVlZ/Uh/Lia9rNRVRTrNdmxSW4veZnbSXmZKq5mm9ZNtkceZNhsVf8vjTFskrbWIIBZpi9c0\nCw2xKHgVKSzvw6IbcpzrY1jF0jUrZ52VUt+KsP9wTuKzNunwSLJtFqbZSDKEUuxnn312ST///PNL\nmnMFYXu0SHi9DBUrbSX6FJm1P89G++rnHGKZsLWQSb0rY6jVzejZW50eEunxrOy6581suSttqte/\n1Y+lD7GXza5bbNzoZTb7PeeDyn1wLLGobpw/LCoQ01wnj87nGGtwjLX1vbUNs58Qi8B5MyLurnFe\n1zlrZtu0jd8j7F3AttuwMdXmG7MK2XzONs32xTl01K7t2dpYYmtOa5fsJ7Yu4f3xvrm+6dZwWr4I\n+zfXeaMoZSfTvFeuUVl3ZsM0ux2/I/Tf2tYW9t3A6vqQSMdR+IQQQgghhBBCCCFsjHzwCSGEEEII\nIYQQQtgY56pxN+uWyZspCzWJWZdgWX4mLTWbhNk2iOVPyZrJ+UY2I5NTm1WJ5z/33HNLmpK9O++8\nc0lXIiZUJOYjq5OVl8cpdSOsO0r1eB0+g4pk2SSyI+lkRV5t9i6TzN8Ma9StQsUSM5L7s1/YucTa\npY0fbEe0EzEf9jse529nLF2W5nUsb7ZpK7vlX4lu2I8zP8pTzeZq4x2xclnZeS2T21O624+zbfBc\nG2/IRZWgV6BEmWO/ScOtn4wsXRXMwsM0I3M9+eSTS5q2XebDNkK79OXLl5f0WmRFg23E5mezeJpk\nvRKhb80eYHlU2q5F46pEb7L87fjavVpZZtvVRe2zZv+ZXQeM6rHyDG1NVJlbZzG7gZ0zOlaxoLHs\nrF+LUMgxkVZRrimZ5jzEeaufwzzMnmLP1yLSViKVEYtUyzKM6tXG5NltHSyK0Zap9I1eF5U1v809\nFkGv0kZsHVuxYPVy2rYpts0K749bp5i1yWxXrDP2E7NEcl3Y05V2afMp651jgG1ZwHWJRZXl+ayb\nS5cuLek+xlg7sXnTtlg4hNujJ4cQQgghhBBCCCHcRuSDTwghhBBCCCGEEMLGeMOidFmkh4pkfITJ\nwkz2RcsTZeeUxr3jHe9Y0pRX2S77FenjjDzSZHWUzDPyicn3TY4+y+gZ2P2bDaUiC+azpJ2Dedoz\ntnZwWvisZyKZXDRuhmy315dF47C6sohSdo5FtDK7kkUFGMlbZ21h7A8Ve1nFImXyXpNj93Ps3ixd\nsewxT4v+YxEYKsd7f7coJZVoNcZF7ZuE4yHHfmtTfF6jsdei2hmVyEEsF6NI0irBMt59991LmpYu\nSqRHlmab18zyUrEfnxWVaHqnZdbSVXmuZC36n60hZufBmag4typn1XZG9VWx59yMtjvLyGpt85TN\n54bZXywqpPU7YpaxbttgeTne2rhSmZNsbmWeHKt5Xd4Hyzsqg0VBnV33W5ThLVOJTjwav62ezbZk\n1sRKRCta8yvry5F9i7/jHMt5mGnC+bliKbPoeGbvsvro+bPu2F+sLLwO87Oy2NrJ1lG0nTNNSxcj\ndo3KaOPUzdgeJAqfEEIIIYQQQgghhI2RDz4hhBBCCCGEEEIIG+NcLV2zmKR1FJHErEKURVHqRsna\nJz7xieE57373u5c0pV6UgNlO2jP2LrOxMQ/K8D772c8u6SeeeGJJP/LII8PyUr7GPE2GZxYp1mX/\nbcWWY9JtsweYpNykbxUL34ytrSKZN5nrrSCxvtWw50xMTmtYf7doUXacEtmRdcqkstYuLVpSJbKP\n1VNFUj3K09piJZqPMdu+LbIa87Hjp73mbCSiiwRlyS+//PKSZkQJ2hfNktrbbCU6k9lJaNFi1Ata\nulhGXp+W6vvuu29JUzLOPjsqQyXipEW7sfSsfcHq6bRtrTL2mR3+kOvbHLo2Jh4y95ot9yJR6T+z\n9Pq1PGbHQ7MfzVr9zaI06jOV9lexhNjYY3PlrNWKlpOeHh1r7fp1tJ1DzLZh5bV1p/Wx0RrI+uDM\nfHuyjFuLPLv2Lnmjc2Z+x7RFleO8yfmU57MtcG7n2pW2IZ4z2nqA/855+MqVK8Nycd17//33D/Pm\nHMr1NfsG74n3StgeGe2r1xnXP7wP2/6E7Zj3xLxZv5yHzD7GOqONi98UaJXrvzU7ZuV9194fZq3Q\nUfiEEEIIIYQQQgghbIx88AkhhBBCCCGEEELYGG+YpcskjibVNOvUSJpesVlRasZIIg888MCSfu97\n3zssL+VYtlM64fkju5TJ0SyazgsvvLCkn3322SX9rd/6rUuaeVJKVinXDCZDrci+Te7HHc5N1l+J\n8GWyyzUsGkNFkrcF28h5cYg9yI6PohLc6JzTUpFC8/qVqIRr9puT17U+MLq/ivWgYjujpJYSWZO7\nVyT2Ixm0/bvV++3SB1kvI8lza9e3u9NGWLHnzzb6yiuvLGlat1599dXh9TkeUwr94IMPLmla09as\neSafNxuIpSvRFw/B+vvNpGK1IiYTH42bNpba+GH1yHZKe8JFYjbCSsXO2+vUxrpKZLaKjWvWzkss\n/z4+VKJJVsrCtNmoOA9x7OH4yOO0k3AM6+fzdzbG8vqcEytbHJDKGGMRGHndnn/FBmg2dYtMtQVL\nV6V9j/pga+P7t60xrK7YXtjmGHGZ73VmhWb+nCtpIeJYOopszOfP3/Hd1yKq0n7NfGzbEOuDlTXd\n6H3L6sJgHmZBN6uqReKlpcsim422irDIZITXse8Y9v2hQhQ+IYQQQgghhBBCCBsjH3xCCCGEEEII\nIYQQNsYtEaWrInk2afjauSY/phXqxRdfXNJvf/vbl/S1a9eWNOVVlYgCMztpm6zTduQfyVBbu36n\n9pstw+xls13FzVpDyRrvg5YuRmpZiwZx8hyzr83A5zGb3xbkr2fNrLy9wuzu9KfF7CFkdszifbN9\nmc21EvFuNN6YlN/GRLNh8reUkZusnWmLiGL2mj62mqy/IoHfch+sWEzNzjOqFx6zdsxz+AwpR2ea\nz5/jPdsa5c+UkjPyht3TzHxqlkmrO4t6VWlTFbtOz/MQa5dZp9Yi+PD6J6lEAurzuFllZ/sd8zmv\n8fysOWSssYhlNxPbMsHmNvstGY3fFUuQRauqWLos0lHF0sXjtM6MLF0WXWm27irvDNYHaNtgGUbr\nbevH9k5kz3TWEnorYmPjrMV2ZE+tjKNsFxZdk9uJ8DjtRyNbVmvXR45i2rYZGfVN2sLuvffeYX60\nJ9ECxrzZT3jfjNj53HPPLWlbR7Kf8JzRe5jZuJkf65Hv+fZeV+kPrAPWGa1eI2sWr2ljBuua/dTW\nNLNczJ4cQgghhBBCCCGEEJR88AkhhBBCCCGEEELYGOdq6aIUyeT9Jq+2HatHMG+zFn36059e0pTs\nff3Xf/2SpnTLJIGUk5ptwiTVo4g0axG9WmvtqaeeWtKU3nEHdYvkYFLNSiSgkSSe8kGmef+U6VPq\n9thjjy1p2rsI8zR5L+Eztkgsa/Jpk2KaPWGmbd6OzEYAISZ7r6TXos20dv0zJf231l9MTso+Yv3L\nLFIWPcMsXWvjjdX7bD0Ss8WYpcuiudj4NMLqrhIJiGzB6lVpI9ZeRvc/G4mK4y5tEpwHCedQjuW0\ndPEclpHtxeyGnbWIXq3dnGhZFm3E2vpZR5CrRNaZveZa5L6ziuCzBdvIrBWrYm+emS8rkerIIXPx\nzDOy/lWJoMff2rxSsRNbmraoUZ5mHePxij2DcJ1hfZb58Hy71mi8sTqtWJrs+Z5XZMGbiW37ULn/\ntWjGNjfZc6NlkJG5OJ9W1pF896tELe552rqRW4LwnY22JVqOmA8tXbRRMRon7WN837N15Kif2nYB\n9m7I69BSZpGuzLZJWAe8P1q6LML26Pq2NYPNFTx/tm9ezFk2hBBCCCGEEEIIISj54BNCCCGEEEII\nIYSwMW6JKF2GSexG8ldKm0xiR9k5o4owKhQjhpg9yGTiJqtbk0jbTv08l9I/lp1yNErmKtGlZiXu\naxEFKhJt1iPldpTqUU7IZ1DZWd3ksqNnZjJXYvJ1s01sQf46i0WX6n2zIjU32arZssxKSCm0RTHg\nOWxra5H1LLqWjQGz0d6snkyGb9GTRjY1lovnsl7MQjMbIaAS+cn6bE+bnNWiAs1GVLqocDykFYpj\nf8VmMhMtimMzpducTymF5vVZrkuXLi1pWroq0uVR2clMhKwbYfOvwTzN/jGKMndIG7V7MnvIbKTJ\nNRvcIRH0ttZPzyq61sy6YXaurDBr9TptVDVe52Y8f2u7dnxkgTJr5lpkyZPY+nO2vBV6Xdq6dNa6\nPTsO3uqsrTduxMiGyDVWJQqizaG0cfEdz2A+XLvxOdq2KKN2yrJzriYWyYtzHNsarWG2ZYKtNcko\nQp7ZMXlvFlmPli7WC9ciNm8Te+e27Uf6/dn7g20PwjTXWodEt4zCJ4QQQgghhBBCCGFj5INPCCGE\nEEIIIYQQwsY4V0vXrLXDLEdrVglKqwh3D6cU6m1ve9uSpkzepHGHUKmDEY8//viSfuaZZ5b0lStX\nljQl87azvEk1Tb42U0bmZ8+A+VFiR2kjdzuvSJNNomkyztG/W34mmV6LWgRDXQAAIABJREFUGhNO\nTyXqlqUpdzSrlx0fPVOTXJs806KQkEpfmx0n2Aa71NX6o8nRLW3jcOWcyrXs/Bm2IDuvwPbK8d7G\nzLV6MUuQWZU4h1JmzD7AKBaUgNM6zfJa+67YtDoVC4KNK7ORruw45eAVafhpqdiPSeX6lbGnX7cS\nXakiNT/riGVvBNbW7FlY3Y6ipFbqsGKpm82nwlqeh7R5i1BkfdPWt+zjNs6N1hEVy1wlClllvViJ\nJDoThdTyq1yHbMHSZc+/0h/WIrJWomLR7mORnTm3mt3RohxzLraImaN1Ga1gNmbwmkyzjBbttrK1\niUXsZr0zAtaondq2CqyXl19+eVgW/pZ1x98yT9rUbE1DaxjTHdYL124WQc7G0JkItyfJm2oIIYQQ\nQgghhBDCxjhXhc/sxsD2lXX0V2Oey7/y83f82vfggw8u6YcffnhYlsomwcT+AkFG98H87C8ajz32\n2JKmMuad73znkrZNo2YVKJW/uPavlaxrewb213xuPs1nyq+p9tdUXsu+jNtfcUf1bvdsm2jZczrt\nZoZbZm3T8tZ8Q+bKJsz8SwrVBfzLBI9b/mv919oI/0LBjeSIHbfN22Y3SiajNmjqA/6Fydqu/UWf\n98S0/dWK59imsv182yS/ssG9sYW+yTZClQyVqayjNYWk1Zv9BYxjNjfdZ99h3+Rfw+65554lzf44\nGptPpkfjRuUviezrLBfHcptjSGWz4YqyrZ8zq26pKBT4rG2T+kr+ZFQ3FaWeUVkXXSRm11aVuXAt\nYEBF3WIBR6wt2LM7reLS/vI8UjLdiEqAlIoKmPXBOhgpgm0MsjGgcq+2MeusqseCVfS0jXd2fRtD\nZ1Sityq2Rj9krOl1UQnUwvUn4fqoEmzINgbmvMx3W9t0vB+ncoZwXWjvOsyPbYT3UVGpME/WB/sm\n1zf9nbCyRjWFj22uzXMs+ATfSaneYV2yvDynb8bNfsRzre7s/YhE4RNCCCGEEEIIIYRwm5MPPiGE\nEEIIIYQQQggb41wtXYbJVcnaRqcmY6dcihK4a9euLWlKzXn+a6+9tqRNumvSvpmNwUwSSPneiy++\nuKQpq6fc72Zw2s2q7RnYxl3E7GCV31bk+R2zhdk5TJvE7qw29z5vDpHtWt31OrKNPa0+K/auNWlz\na9dLmiv5rD3fygbOlc06K8dnYT79eZi01+xdHLN4nDAfyl9p1zJJr0nlea1+3CwxFUuXjb1b2Fyd\nYyNlwbRIse7Yvkd93MbA119/fUnTusV5iFJozkPsd5Q88xybNznnsgzsjz0f9mMbg2xsMMvCWW2c\nTkbW4UP6fcUeYptukoqNa21tdlbj10W1jVSCShhr86adW9lMnOdbAA1i1i0bh227g46tgyqWLhu/\nbVsHHueYwDJa0ILRcc5l/Hebe6zuzNJVsaxX1jejfCyPyphhZb+ofdOwtVtlLFurC5vXzHo5uzWE\nrTVt3uTc3ds13x9tzrI+QKsS+69ta8A1IjeTtm0FZqxhdi4xy7GNQxWLrNnBLZDLqOyVd4lKkIlZ\nLv4KOIQQQgghhBBCCCFcRz74hBBCCCGEEEIIIWyMc7V02c7cFdYitZiFiLJzRgy57777ljQlaPyt\nSca5CzihfH1GDm52tM9+9rNL+pOf/OSSpmzz6tWrw7Izn7VoJ625tM/kY73eTZJoO773Hctba+3J\nJ59c0pQeVmT1zNPKa7Li0XGrO4uOUtmlPxxhu+OzDs1aZRE1TCJtVgamzyJKl9mTLEIgYX1UIhpU\nWJN5mrWKUuBKhESW12S8FUsXj4+ielUipZjs3MayLUTpMrsUj7M+18b1kRWwNZeFUw7OedCsBrRx\nWbun1ZrzAyXgoz7LPl2Jsmh9xGTcFat5hbOwRJjUuxIlk2OcleW00bMqdWRz+FnV7xuJRb2qjOWV\nSE+jcyuRlUjFqmK2WYvIVrGAjX5XWTdVxmmbE2httXmrYg1bK1fld3YfFm2UZee4OZO26HyVyGCk\nYpe91als2XBaKpGaK7YdPi9b25i1iNfiHMooznzH6vP1pUuXhvlxPmV/YTvjb82WzzUl53CznVnk\nr1Fd8jo81yLGksrcx3Zi9W7RUXk+729mbCeVbwizluoofEIIIYQQQgghhBA2Rj74hBBCCCGEEEII\nIWyMc7V0mVyKMi2zVdiO912+ZfLN559/fkkzMtcdd9yxpCk1M3kVJVqUnbNctIxVJH+jcykd++hH\nP7qkP/axjy1p7pR+//33D39rdT2KGHLyHJNCjmwTVl9m6aLdgHLDxx9/fEnzmVE+x7JTSmcSZKPf\na0VqbDausE5vGybTZJuz6FpmTeBxy2cmusXJ9CiaDscVi+4wK1k362VFwrnW7k2qyr5p/ZdlZ9qs\nWKwbSmqtP65F6ZqJCHPy/C33U/YNyqvZjmy8X6sXPhNKsWnponScz5ntyPoUz+F8+swzzyzpZ599\ndkmzfXG+ZlTNEdamLVqgSbcrVCzSI5vYrIXJ1kKVCGM2h1nZ16TklfyIWRsqUS9vdazcledra6u1\n/Pg7s5+T2fGQz8hsuBblZhSZ08amyjxhbdEsWmb54LhpEYj6eGMRvUilTiuRR5mmpcvOWbO1WwRS\nK0slStdF7Zuk0h/NgjfTT0klApf1DVv3EpaFVmtauh599NEvO853J75fMc17vnLlypLm2MD5mfM5\n1wi0fdt60bY0GfUx/o5prld4TY4Hth43i6dF0GP9mT1uZCurRPaz8ytRxSpsd2UcQgghhBBCCCGE\ncJuSDz4hhBBCCCGEEEIIG+NctXpmDajIgilPHMlCTbpFqRulW5Ro8Zq8DqnIwWejNfXzmQfl87Q5\nUSJmdjiWkbI2SvUs0lVlR3kykj/yXJbF5HsmVWQdUJ5IKH/ls6Q9b42K/cae9e2IRVgxRnJDs2Kx\nLZiU0aSwZg2wtEk1R9JlsyCYzcjKy/5r1i2Tz1cioozqmvdjlgCT1Zuly6IhWFQtu1eL5NWP21xh\nVi+LMkMuarQRYpJ+UrH9jaJ0sc5Nos1nbjYFi4xl1gvO0bR0mYVyzb5IKpH1TFZfGeNmbFyVPGaj\nbvCZsb6s3502GhexcdjGm0r6omJrgtm2szY2rY31rfl6anbdYteyNftoDmFZLGqOzZU2ZvGanLfZ\n7is2Koty19PsU5X3AcP6iVnKbWy3SKJnsR6dHW8uKtZnKvc/U88WpcvaeuWa9p7CNC1NL7744pKm\nXfqxxx5rrV0fdYvbkDDN9sf3MfY1vmvxHIvSZWMc+7K953dYp7SIMRo31yu8vkXjtnc/9sdKBD2z\n8PWx4qzagK3TK0ThE0IIIYQQQgghhLAx8sEnhBBCCCGEEEIIYWO8YVG6zCphUieTR3Y5mO0Y/rnP\nfW54fUrHKMvirttm1zKJJZmxD1CmRmncU089NTyf5aLEzuqOZWfdHWJX6mWu2ML4PCqRiChDtAhM\nV69eHR6v3Ed/ZhUbl9nbTLoZvhyLPlCRXB8iW65ERjA72Kh9W362+75d0+xadtz6jEVomYmsQ8xG\nVbFXVSxdlchfveyV61Cia/YusgVLV6U/WCTGtYhdrFvOp5Ro85y3vOUtS5pRtMwGYZZfyq4pzWbZ\nL1++PMyzY+NxxUZ+SEQa3pPZMEbjTcVaZVYvi6Jklq6K7LsS4avX02yULqujLWD3MzvWjKKwWVQs\n+53V/2wktYol1qLGjZhZk7Xmc+XsPGsWwzXbl0VBs2dasYeYPcPWIpVnOSqDjQ2WR+VZb3krg0p0\nwtE7UyX6pUWlsnZkESL5W4uSxTz5Dkl7V49+bFFa+Zxps6LlmmnmzcjVZu8y6yXnSq4p1iKVcdsS\nKyPP4XuorS95TZaFaX4jsCikozU7j81a8+1dfXaeicInhBBCCCGEEEIIYWPkg08IIYQQQgghhBDC\nxril9bW2MzUl4z3NY5RxfepTn1rSn/nMZ5Y0pVhXrlxZ0vfcc8+Spm2IknWmmc+svKqfb3Itk8zd\nddddw+OUhlECP2s5sogJZCRjtN3kab2gnNDsMrxvSukYbYz5WMSkNUxCa3L4s4hwcqtSabtmcVyT\nH5uEuWLvqliqbga9PBbVzmxns1G3LMqeydR5TkWOPDrX6rEiUzYJsNlliEVfGUniK5YuoyK9v11Y\ni5Bkz4TyZ1quWP/sp4xiYbZhG295XcrUKxaHGczWYWMMqYzxzJPz1mjOs+tUWLNDtubPvXIfVu89\nbZHBmDZ7whYic1WYnZ9G58+OV5W6PSSCoc1za+tFqwubW836YfNAJTJnZd3R0/Y7qyOLamaR+g7p\n+2Q0DpjtjlSi9s1Y9i4ClShwthYa9UN7hmy7nMsq0VBtvch8mLZ5gPMN7VX9t5y3eS7tV5z/aZF6\n+umnlzTfPbtd7GSa+bBuLOIe581RNDv7JsB3fr4/ju7/JGzrZuniuyfLW7FqrkVEJfyeYG3wkPfN\nKHxCCCGEEEIIIYQQNkY++IQQQgghhBBCCCFsjHO1dJlEiTIqkz5apJougaLMivKuJ598ckn//b//\n94fXefDBB5f0fffdt6QfeeSR4XFe6/7771/SlLWfFpPpUVb3kY98ZEm///3vX9KUso3kcK3V5KQV\nyedaPmbJYJpWgVdffXVJP/vss0uaUjqmKQ+kXNIkdmt2lYpFac0ecZGxupplJAW2Z2KS50p9VuTV\nlbRF/uh9oBLdy+TCZsWyXfkrNi47vmZrrEQpMdmoSdZnj7Of2vPuZahYzaydVqIebJnT9rGKHN0s\nhZwTzc5jZeRzsaiTo/uw529zk9k6zJpoNslKNBfOv5SG97m4MsbN2rIsepZZGCqW0LWoP9ZOLIJg\n+BJrkbfOyoJ6ntEJR/dUaX8Vy3ElGpedzzTXw6M51MYAUrE5VcpSqYPKerRTqd+1PE4e31p0S45T\ns5GQ1t57LNKlReyyNZxZl5gP7VhmGVuzEdk6j+9mtGgx6rVF7GKUZbN3sQ9y7cCI2Xyf7uezvLxn\nvvMz0iePs75sLOH1Lc2yW5TqmWiU9n5k+dk6ukIUPiGEEEIIIYQQQggbIx98QgghhBBCCCGEEDbG\nuVq6TOpNybNJ5kxW2OVQJq2iDYh5f/SjH13Sn/jEJ4bnv+Md71jSb3vb25b0Aw88sKS/8Ru/cUm/\n9a1vXdKUXZl9bSSxsyhWlL19/vOfX9Kf/vSnlzStUCwjf1uRfVfo55v006KX2a7plARShscy3n33\n3UuakdLMjrVmBanIX01+a2whosFFgPLTShQ4k1SblaG33zXZfWtuX7BzLNJUxXZmUSXIaKw0uTjT\n7LOz5SKjCAUn02tWObtOxb5pc8XtYi2pRMYajWVmJybWjmhhqkTpsnne+oY96zWsnZllkLJ6i0Rk\ndWD3Ooo6eEiknko7tjFxzUrZmvf3mWg1tzuVdQD72Fo0KKvnihX9rKhEb+3l4b+vRa/h726EbQ3A\ncrGvWTteiwBZGfsqFm1bC3BdYvaQSiSgUV+uWD8rFq0t9GtbN1Wikc5E+rSxnsctmmHFLm1js0XA\nsjGhl8fmALOjMRoX65RRvWjdoqXrueeeW9K0ifFdjvXEPjCaN1le1h3Ly3Lxmmblo3WM98c+yLJU\nxtm1rQdsTLR38rXxtsrF79UhhBBCCCGEEEII4TrywSeEEEIIIYQQQghhY5yrpWs2+hGh1Iuypy5X\nphyNMklariw/Sp4p47p8+fKSvnr16pK+cuXKkr7nnnuWtMlYjX4OZVncDZwWMUYDo0yNcjAep8TP\n5Iyzkto1bEd42/3+oYceWtKU4TFqGuuXdWOSuUp6VN6KfG4LMtezYia6REUCadECzLrFdsS2bjvx\nV647kk6PbF43+t1sZIyK/ckiYFlfXqvvSsQuO39WJm5W2zVriVlFzVZQsRvcjpauGSrjntkRaMte\nsy2fxCTrFRviCGtn9juOK5yHeJz3av3BIlaRmb5px22uYj9hpBJGU+GahvC+aammbaDnb9aTSrTV\nrTETjaX62153s5GgKtc5ZAy0347G6spYXxnXych+1VotoiXTa1G6zNZp6/vZ8dbWC/Ysrf/MzPm2\nfYFxnlbB8+aQ8ag/I2sLnAetTVeshjavVOY2roHZlvv5bP9mJeXvODfw+pwnGGWZ9i6LVGZRt9es\n0DYPc75l2t6J+Vteh3Vgax1i54/eJSyKpY2DtpXBIWx3Jg4hhBBCCCGEEEK4TckHnxBCCCGEEEII\nIYSNca6WLpNFVWSpFuGry9coY+Ou29/yLd+ypN///vcvadqyKEczmwCly5cuXVrSjOpV2f1+JFel\nfJLRp1heSqvf/e53L+kPfOADS/ree+9d0pQWWuSTQyxdI8uLyRaZN+Vz3/RN37Skr127tqTf+c53\nLmnau/hcLaJMxb42gr8z+0Bld/+LyllY+lob17NJVSv9nv36tJHkqumRBNdk92zHxCJqWJrjmtnX\nLLqAWWf6+RUJ/prt8UbnWD4Va5ClRzbASlQkkzrbfWwZs/POWADYjjmXcAzm3MfjNlcbFduESZ1H\nv6scZ71Q9s0okmadZt1xfLLoIKT38UqfIpX5js+dNq6nn356SfM58Z4YiYXrIUb+7JJ8rlGYhz33\nivX0otpGZtu6YXb4NSwSUeU6h+Qz8+wO2UbALGBmn+Bxs3StRe4zu4Wto60NVCJqklmr1do1K/Y5\ny4/t5BDb4huJRTSz9xRi9tSe5lj7+OOPL+lHH310Sf/kT/7kkmZkZc4Zd91115K29Qzr/8knn1zS\nfCfkObTzchuMfg7vjWtLmxM5r9ESbOt6s1VyvcCtOvguzujSvFafe3j/tI5xzmKaNjLC9Tu3S/nm\nb/7mJf2+971vWC4+M7NRj6iMTaQS3bAyVl+X59TZIYQQQgghhBBCCOGWJx98QgghhBBCCCGEEDbG\nuWr1TPpo0jtiMuougzO5FCNdmRWLMm5K9ZgmFpHEOK39513veteSpryN90+pGW1nFq2oEl2gIrUd\nRRgjJh1m3fH+eD6fk1lnKGesMJIVV6IuWJSh2yXizyH0erQobWyjJl80y4JZBmdtXGRkOa1YENZ2\n5z953PLnPVFSy99aFKPRPVkEHxtvTR5qdpJKRDyLQmHn93PMtmJ5VKT3s/LXWxGbH/msKdM2efUa\nbCPsF7TzmKXLrlOxD7IvjaJ0sGyzkausD3IcevHFF4dpqw9apyjpZgST0Xhm7dj6ZqXuCKXslMFb\n32DZObdSHt/LxrXIrB3NLLQX1TZyVpyFpe2QOrTrWwQbwja7Ng+ZNcEsZbYGJ1Yui4Zka4d+vJKf\n1RfPqbRvix5mFrS1dwk71+raxkRbL1wkZi1ylWhovb44Rj7xxBNLmjauH/mRHxlexyIbGnwWzz33\n3JKm3dYs1bR09fZlUW0J749pqy+2XaY5flgEbFqqzNLV+xXtZZx7OU9ZZC77RsDrP/LII0v64Ycf\nHpaFdW2RyvjMen3Y2FeJQGqRFmffQy9mTw4hhBBCCCGEEEIISj74hBBCCCGEEEIIIWyMc9XRmsSu\nIkWlVJKyri7ZosyKmCy8UhazE81KHGeiO/E+uZM5I3ARlpFSNuZjESAOkRH3PE3majYMyvqI2VYo\nOeRveS0eN7k78+ztwCTzZhW4qNLWChVpYEXSPcrT8jZ7AdsC5aEWfagSHc5gf6d0td+TRcIyu5aN\nHxVLl8lrzQa3FoWrYq0yqbvZYmgXqliq7JnZdfv5PEZ7CvOzCBO3u6XL7EKj9lKxLDJtEu2KVWMt\nMltr1/c39v0123dlLjObBPs9JfOUw7PdsVy0fTHSFaXeXJusWV6MSmRBs8VYBK5Kn+Hx/rwr0W8O\niQB6kTirMcXqfw2rc+uDxuw4YDau0ZrZ1vdmf5qNbkVmLQ5r+Ve2Q7C1CGEdmM3W1gu2Zub5PV15\nf5m1/m3NbmntuEJ/1nyGzINzBo/beuYQzDplbbNjY4O9U9kYx3Zh22CwPlhG2sGZpnWKx/u6t9LX\nbK1r6xiLlGtbSFSi5p6W2e0WpvM/k1xCCCGEEEIIIYQQwi1DPviEEEIIIYQQQgghbIxz1epVoncY\nPIf59DQlWhV5MmVZJvVm2mRyJj81ifmahNTyM5sLZWQW0YDHzaI0a9fpx233cKu7iu2L5eVvbcd1\naz8m5+v5VCIqVSLBbIG1iE8nj1cisvRzKpH3DHu2bAvWpyidNdsV7RyjccD6oNlTrH/N3utsRLK1\nnf75O9rCLCrhWiST1mqRtKwvm6Wrl80k0Gb3tLzJFixdFSrWqdNi9mBrF5yXK5FiLJLG2thrY5NZ\nIxgtklE6adEitJHznuy3XF/Q0tXn7hm72slz7J4on2efYVk43vFaLA/Ly2v143fddddyzJ6vlb0y\nbp5FOz0vZqOFGqNxvTJvnsWa8+T1iY2Zlet2bN1vc7JZnpjm2G/rd/st06Pxhm2a17E5i1Tqy6is\nRy2qV78Ps4WZnaVi2dvCVgZnYeNimmOq5W1jsD1be2eyCLYW+cvWiP0412TMz9Zq9m7AcyoR5mjR\nunbt2pJmJG1G6eL53Yps2x7YWtjKy7nSokLb+7H1/Uq04M5ZzXGza9qL35NDCCGEEEIIIYQQwnXk\ng08IIYQQQgghhBDCxrglonRVZEmUV1Fy3GVUzIPnmnSa8ivKuCoRBcy6VIlYMSpDxUJTkdITs6CZ\nhNAk+bbr/6ieTGpsFg/mZzLDSkQSYr9dk+SZJNHyYJq/3QKVSECV8/txkyTP2heIWT8qY4zJa0eR\nZfg7ykmZNnkvy1jZwd+iTllUAB4n/bfsU5QX057C4xblby3qw0lmI4KNrLYz51bLtQVLV6UPmjVg\nLT+bY+z5s32x7VgUEsrO2QYtWo9JqmeiPjEP2rjuuOOOJf3SSy8t6ZdffnlJP//880ua98r7MBsk\nr0XJeJepm3TcYL1Qjn716tUlzXmI9cuxytYCrA9atkZR0+6///7lmEVHJZXx/KJiFoNZTmvpIrYW\nvdlRlk5r+WF75f3PRuyatUuZ5aSXh/MK0zavkbOyJpqlyso+snSx75pt1trMFixdZu2pwLoYPXeb\ngyrXqWzVUTmf98cx2+xg/bhFomJbN9s/MRsw2xfnyitXrizpt73tbUv6oYceGqY5h/b7ZpRJW1+b\n7Y1wvuN8OrrmyXzsnYCcdp6rjBmHzKcXsyeHEEIIIYQQQgghBCUffEIIIYQQQgghhBA2xrlaug5h\nRsZt0vQ1+8bJ9GxknZnIBSynSVgr8kA7x/Kp2MFs5/4Zuao9r0o0Bit7RdpasZWN8jsrbrZ8+mZh\nNjYyayfpMkuTrfKasxJis20Sk2RSumr9oUs1aVWx6B6UUdv1rR3beGN9k6z1QbPcMLIMowyZZc2o\njE+z9q61fzdbJdmCdcuo3Bvb5lpUJLMmVsYAPpcvfOELS/qFF15Y0tYHn3vuuSW9Finv5LVG7aVi\nD6W8nBFAKO9mP2Fd06ZmEX+Y/913372kGYWkH+eYNRsJ8p577hlen8+Sz4PHbazmGEZZ++heWV+8\nZ8Mic551BLk3gkp0S2Nt/JqN0mVr0Vkq829lfdepzGWHUKmnSoTAUdkrWzPcDKxvrEUUrtyb5XdI\nNNVbkdktNipr0FG7tzq/fPnykratLCpWO3un4NjL6FZGz8ds8bYWoI2K8yDvz+ZW2qVYRrN08ZzR\nOyHt17wO5yza22xrBJ7D+ZT3YZZyqycyans2P8y+M669196IKHxCCCGEEEIIIYQQNsa5yhHsL9uV\nv0bY19rRF9fZzcfsr2pWLlMEnQX2FXBWhWR/VeNv7et+5Uvz2qbNxBQ7piqxv8xU/kpjz3ikAqps\ndGrPY2Zj1K0w+5eeXi+2oZr9pcOUMfYsrP7t67dtysi/7vc8Z9uZlYtlqdRjZVNy+2vfaHM+/mXG\nNnCu/OWCVOrA1Dm2Gfrod5WN6W8XDtm0eTQnsC3wr5D2V2ALgsC2w42P+WzZv6hAIVSPWJCAUXup\nzIPcWJJ/1bNNpu2vsvaXRf518N57713S3OS435+thSrzIK/PNH9L1RT7j6m/KkrlnjZlZgUbky/q\nZs5r7fIkFZX0zVRUzP412daRxoyax9SaNmdUNlOuKBbWAhJYMADbuNXqxeanSp9hP62sh0eBGmyO\ntU1tK5uBXyQqakJ7v7HzR2Mgx30qRx555JElzbZoG2vbe5e1F+bz9re/fXgO20DP39TunDNYXs7b\nVIRz7qOSh2kqXe+7774lTSUPj7P+WAe9bKbM4Xxr/Y73xzmZm0lz/cHrmyvA6pJ109uhvQPMjve2\nXqhwe7yphhBCCCGEEEIIIdxG5INPCCGEEEIIIYQQwsZ4w3aYNTnxaalsZGQbOJOKheQQOdZpNyo0\nGSKZtZqZjNsk3Sz7qAyzz6CygbPlb/VRsfP1Msxu9kfsPraA3fOsfLA/04qE2exJlf5o/WHWUlUZ\nH9byNirXr2yyOGOxZH1RokvZNy1d7IM8h8yOdyaJN7l5v7+KNWDLmzMblfqv9Lde/1aHZr2k7JwW\nqcoGy0wzT8q0rU1Tat3rgPmt2ZBau15mTQk468s2fKSVjZJ15sm64Tm0XfXy2ObXpGKlsPUE6+uN\nprLZ7VltOHzezI6Hh6wdO2e1OfQsM1aCNcvuyeOVjfktqACtFGZR5Tl2vOdp9q9KAIKK1YuYdYv3\nZ3P+6Pjav5/EjlfeN251rNy2bUfFxtz7AMd9jrWXLl1a0u973/uWNNuCWbcqNi72Qc4x3ATZxph+\nT9anaLO2gAxm6TLLM8vIOZd2LLNIsw76WoPn0hbGfs9nwL7Oe7p27dqS5pzP8lpAF1vLr220Xnm/\nsP5o29jM9s0ofEIIIYQQQgghhBA2Rj74hBBCCCGEEEIIIWyMW8KLYhG4jNNawExGdZ67ZK+V3cpS\nscCZ7KtyvkWmMhvXmoXEpG6Wt9m7iMkfzQK0ttN+xf5Veb4XVfJKKhaaSoSRkTWPx6ye1+yCJ8+p\nyCPP2jY6m3fF4mh5Wh3MyLRNVs/yUvI6E0WrikU2WYtGaG2GVGzBY5V7AAAgAElEQVQxW6Ni16rM\nZ/0ctifKsiltHlnuTp5D2TvhM+L5Zg3jcTKaK/jMK9Jq3t/ly5eHxyk1JzyH92rWSzI6bvbJyrxm\nbd0icFXG7Vkr+8y/m1Wics1bHZP6V7B+1etr1ips+VmEplkq43fH1shMWzQs9gezVVg0LrN68Tjz\nGVmdLcJdxdJFKvVl1mliY8LIGlSJ4lnpj2Y12xq25rJ5sdcR/502I0al4nxnzGxBcRKWi/Ymlo1z\nVX+mFjnz1VdfXdIV279FdqbFjccZDYt1xjLaurffK+dtG+8Y9cv6/dWrV4flpaWM44C9T1feZ3o5\nrT+SmW0lTkMUPiGEEEIIIYQQQggbIx98QgghhBBCCCGEEDbGLWHporzJpFMmoVyTpq9Fg2EeJ9OV\nCCYV65Qd79eipK0i4zVJpkUtMSgZq8jURzI1k6pa3pQNWiSCNdnqyXLxOHdrZ72P5O4VOd5sVI2L\nGjloNsJbhYpceURF5koqlj5jxo43G7nCzqnYKuwZmP2DrN13xepVoXL+jA2AVGy+sxFRbhdmbF8W\nXYN1/uY3v3lJW7SqWasZx2Mb48nIlmS2JbMwMV2Rkc/OA5X23c+pzJuV+2O7P2TeMs4qn5uV3xsN\n7Q6HMJorK+2JtiVrF2+EXc4sXVyjVqLg2LrfImlxTWk2MbN69XMqUQYrUboq9V6xg1XWvTNRuirW\nkso5W4PzkFl7+nHWDy3JtByZxdb6htnrKhYi2qV4Xc5zfa43Sxfvme9pXBdwLcB6Ydl5fYvGybVD\nJTLVyNJlUTzNgsZ+bxEtWQccGyrbpVhE0F7flX5k+Z2VvSsKnxBCCCGEEEIIIYSNkQ8+IYQQQggh\nhBBCCBvjlrB0zUqk12TBI+vRacpyVlJYk2OPrEVmbyMVawulbJTh8ZxZy8vMDuIVuTYldrazvFl0\nZu1zo3y2ICk/KyqR59YiK51kJFc2+eYoutdJTBJZiepWGWPWIqWYdeysqNhS7HzSpemU1pq9zmyz\n7GtmFa1Yuio2tRGzEWouapSfWSr3WbHN9OdrcwPH4EuXLi1ptin+tkIlihPTa1ZoYn2HecxGczQq\nFkPLs//WbNkVe1nFtvFG2LhsHDYbyhbmX8r+D2FUF4dYZt/oqIW2njALsVmnLKKkRfgyqxePr0UH\nM0tZJU0OmcNs3CKjubgSqa2y1tqCRdreV+wdb8Yib/Mg04zYZWsxW+dZNCwrL21XtFGNtscw25D1\nWd4/1wLcPoPYdh6sG5tj1t75mQfbLi1itKlVxoPZeXN264P+DCprm4ql/ZCyROETQgghhBBCCCGE\nsDHywSeEEEIIIYQQQghhY5yrpctsQJXoN2vSpdldrG0H7EMsXSYHswhU/fzKTu1mxarIECnxs13e\nKXczefyaHNvqzuR73OWdWPQXy7MiPx3JWK0eK8/xdqdip+n1W5EdWhSJCpXnUunLa+WctSCYdHp2\nXKmMm6TXR8XeSEuCSaBNglyhYhVcK+PsdUIdi1xl7bUSRapyLZtjKvPNWqQr6xenbYsnz5/Nf1RP\ns2sem0OtjszCYmW0PNeiJHKMM9uoje1mYWHUlFudm2HpmrHTmIXHnvNZrWHWymj/Xom8a1avym/N\nMjazBYD1tYollX1gdryZve7aOw/rwuwkVi8cMy4qfBasK7MxWzsivb7Y72nXeuihh5Y0IzVVrPN2\nTgX+1qIfj2ye/J3ZuC0CNuvRLGg2l5jNk++EbIP9t5Yfy87nQduZWbpYB4xOZluO2NzO+hhFfKtY\nwSvRwMjseB6FTwghhBBCCCGEEMLGyAefEEIIIYQQQgghhI1xS1i6bDd5O055E6VTM9ecjcwxG5HG\nfjuSYFVk8mYLMxuGRfWoRASryAlH0nRSqVPK7Xh9lpcSQrvX09o5TB54MyK13epU5INkRnJq9WzW\nrVl75iFYtJwRs1Yzcsg9VcbNNUxCS6wNmDR8lpk2M2vBO88280ZSqf9K1KvR+G0258r1K9HYZsfY\nNevUbKQts47ZNSvnV+bukTVr9jqViDOEsv5XXnllSVek9xznuL4aWXQrli7K7TmfUzLP8l4kS9ch\n0bDM8jOznpmNfHdW4+SM/fmQrREq1qaK3dLyX7O82O/suK1LZ+dN6492ztpawK6/hWhcBp+nRW6u\nWNc5BvbfWn1yOwpi7zeVcpGKLcjue+2djdCedMj7KanYKvlOyGhbfQ5huazfV47bc+ecZG3A3mE4\nb61Zoa2tVSIBHhLp8vZYJYcQQgghhBBCCCHcRuSDTwghhBBCCCGEEMLGOFdLFzGbB6Hsae38ikS6\nEn3iZth57Fo9vRbR40Z52HVmd+U/rS3KymhYlC5en7vbm+TUJG7EJOZr5TRZ7pbtXYdEOZqpl0o7\nPiSSCNuXSbQrEumzLlflt7M78W/ZxlRpj4nMdXpGka4q0WDMemLyY1KRIlfm8RlLV2VsqkQMszJW\nyr5m6TYqUb/smhz7KJMfRT5p7foxkRas0fqJz5dzrI23ZiOnjYtlvF2w6CwzNptDbMZhPdrseTK7\nPcKaVe92nx8r75X2nkRG/dSsWGbjq2xVcoi9rmLzXbMTk4qN38predoYV5kT+zlra4KTac53VteV\neb7yrmJrqTWraGUNVokMWmG7bwwhhBBCCCGEEEIItyn54BNCCCGEEEIIIYSwMXZbtqmEEEIIIYQQ\nQggh3I5E4RNCCCGEEEIIIYSwMfLBJ4QQQgghhBBCCGFj5INPCCGEEEIIIYQQwsbIB58QQgghhBBC\nCCGEjZEPPiGEEEIIIYQQQggbIx98QgghhBBCCCGEEDZGPviEEEIIIYQQQgghbIx88AkhhBBCCCGE\nEELYGPngE0IIIYQQQgghhLAx8sEnhBBCCCGEEEIIYWPkg08IIYQQQgghhBDCxsgHnxBCCCGEEEII\nIYSNkQ8+IYQQQgghhBBCCBsjH3xCCCGEEEIIIYQQNkY++IQQQgghhBBCCCFsjHzwCSGEEEIIIYQQ\nQtgY+eATQgghhBBCCOH/Z+/Ng3TJ8rO8k2gkjWbpmV7u7e327Z5uqdGMGBhpQoTNsDnAxtjBYssQ\nYBkpTGAIFArjjcVmsQBZBoHDOABbAcYgJGODsDAmsIyNrQDJMtbiELMvmt73fZ2ekTR8/qPq5Dy3\n+jw3f1lVt7q+7PeJ6Ohzs/I7efLk2fL73vf8QggbI1/4hBBCCCGEEEIIIWyMfOETQgghhBBCCCGE\nsDHyhU8IIYQQQgghhBDCxsgXPiGEEEIIIYQQQggbI1/4hBBCCCGEEEIIIWyMfOGzZ0zT9DXTNH1+\nmqbvX/GZ3zZN06emaXppmqanpmn63mmarsPfb5im6e9M0/TqNE0PTtP0b16b0oewf0zT9O3TNP3k\nNE1fmKbprx3526+ZpumT0zR9bpqmH56m6U787YemaXoF//3sNE0fWXntt03T9F9P0/TMNE0vTtP0\nj/G3r5ym6XumaXpymqbnpmn6e9M03X7iGw7hnHKkP70yTdMXp2n68/j7b52m6RPTNL08TdPHp2n6\nzfjbd0zT9HNHPn/3imv/c9M0/R+Hfe3paZp+YJqmW/H3dx/OrU8d/vcdRz7/y6Zp+vHDsn14mqZf\nfsLqCOFcM03T90/T9MTh2vPT0zT9rsPjXzFN09+epumBaZp20zT96tPKG3+/2tz8+6dp+uhhX7x/\nmqbff+KbDeGccrU1LM75Y4d98dfi2InXsAv5L82Zf3Kapo9M0/TzR/8W1pMvfPaPv9ha+4mVn/mx\n1tqv2u1217XW7m6tvaW19p1H8vzZ1trNrbVvbq39N9M0fd0plDWELfBYO+gv/x0PTtN0U2vtB1tr\nf7S1dkNr7Sdba3+z/3232/363W73jv5fO+iHP7Dy2n/pMO/3Hv7/38fffl9r7Z9vrf3i1tptrbXn\nW2t//mgGIWyFI/3pltbaa+2wTx1+2fn9rbX/oLV2XWvt97fW/sY0TReRxd9kHrvd7r4Vl7++HfTH\nu1prd7bWXm6t/VX8/b9srb3t8O+/tLX2O6Zp+rcPy3ZDa+3vtdb+TGvt3a21726t/b1pmq5fcf0Q\n9o0/1Vq7+3Dt+Rtba985TdMHD//2o621f6u19sRp5700N7fWptbat7SDPv0vt9a+fZqm33bMcoRw\n3hmuYTvTNN3TWvstrbXHefyU1rCaf7vKnHnIz7TW/kBr7e+vvWZ4PfnCZ484nJBeaK39n2s+t9vt\nHtrtdpxUv9ha++rDPN/eWvum1tof3e12r+x2ux9trf3d1trvOJ1Sh7Df7Ha7H9ztdv9za+3ZI3/6\n11trH9vtdj+w2+0+31r7jtbaL5mm6WuP5jFN012ttV/RWvvr1ese5vMbW2u/e7fbPb3b7b642+1+\nCqe8p7X2D3a73ZOH1/+brbV8URveLHxTa+2p1tqPHP77Umvthd1u90O7A/5+a+3V1to9p3Gxw3x/\nYLfbvbTb7T7XWvsLrbUP4ZTf0Fr7M7vd7nO73e6B1tpfaa39zsO//bLW2pOHn//ibrf7/tba0+1g\nDAlhk+x2u48e9pXWWtsd/nfPbrf72d1u9+cO15tfPM28D/991bl5t9t99263+/92u93P73a7T7WD\nNe+HWggb5Cpr2M5fbK39wXbww/+Q46xhC/lfbc5su93ue3e73Q+1gx9XwgnJFz57wnRgwfoT7eDX\ny+N8/pdP0/RiO+g439Ra+3OHf7q3tfbzu93u0zj9n7a8OIawxNe1g77SWmttt9u92g5+kRj1nW9p\nrf3I4aRW5Ze21h5srf3xQ0vXR6Zp+ib8/a+01j40TdNt0zS9rR2o835o5T2EsK98a2vtr+92u93h\nv3+ytfaJaZp+wzRNX3Zo5/pCa+3D+MxvOLRkfWyapt97wuv/ytbax67y96m19otO8PcQ9p7pwJL8\nudbaJ9vBL/z/6xnkXZ6bp2ma2sGL7NX6cgibZJqm39Ja+8Jut1vql8dZw67Jv7XMideUfOGzP/zJ\n1tpf2e12jxznw7vd7kd3u9272sGvoH+mtfbA4Z/e0Vp76cjpL7XW3nnMcobwZuEdrbUXjxyzvvMt\nrbW/tjL/S+1g8nuxHVi2vr219r3TNL338O+faa093Fp79PC6720HXwqHsGkO9+P4Va217+3Hdrvd\nF9vBr4//Qzv4oudvtNZ+z+HLXmut/a120EcutNb+ndbaH5um6bcf8/q/uLX2x9qBbazzv7XW/uA0\nTe+cpumr28EvlW87/Nv/01q7dTrYT+/Lp2n61nagRnhbC2HD7Ha7b2sHc+KvaAc2qy+cQd5r5ubv\naAfvQn918LcQNss0Te9srX1XO9geYInVa9hC/lebM8Mpky989oBpmj7QWvu17cDvePRv3FTrmw//\n6/9+3a/9u93u0XbQyf7Hw0OvtIP9Dsi7WiR0ISxR6juHm7Pe0lr72zj2n6Cffs80TZe5Od7haa+1\n1n6utfadhxL4f9Ra++HW2r90+Pe/2Fp7a2vtxtba29vBgjcKn/Bm4He01n50t9vd3w8cbgb53a21\nX91a+4p28IXQf3s4f7bdbvfx3W732KGl6sdaa/9Va+3fOPxspT/263x1O+hnv2+32/0I/vTvttY+\n3w6+iP277eCLp0cOr/1sa+03t9b+w9bak+1g35B/2P8ewpY57HM/2g5+xLiqsm7U946ucwt5V+fm\nb28HL7L/6m63O7UvokLYE76jtfZ9S6qdE6xhl/LXOTOcPm95owsQSvzqdrCp1UMH6tP2jtbal03T\n9L7dbvcNg/P/+4X83tK+5HX+dGvtLdM0fc1ut/vM4bFf0iJvDWGJj7UDW0lrbd4P6572+r7zra21\nH9ztdvOL4263+6528MsHeceRf3+4vZ4d0h9orf3h3W733OH1/3xr7U9M03TTbrd7Zs2NhLBnfEs7\n2LSVfKC19o93u91PHv77J6Zp+n/bwY8lPz3IY9cOJOTV/tiVRf+wtfYnd7vd912R2UE//Gac+12t\ntR/H3/9Ra+0bD//2ltbafa21/+KqdxnCtuDac8hut3uoHel7u93u16/Me3Funqbpd7bW/lBr7Vce\nVzkfwp7za1prl6Zp+rbDf19orf2taZr+9G63+9M477hr2KvmvzRnhtMlCp/94C+1g8nqA4f/fU87\n2LX811U+fKj6uXyYvrO19p+1w42fD+XuP9gOXhTffvhN7m9srX2f5RfCm4lpmt4yTdNbW2tf1g6+\naH3r4Qvb32mt/aJpmr7p8O//aWvtn+52u0/is1/VWvutbb2dq7XW/nFr7aHW2n98WIYPtdb+hdba\nPzj8+0+01r5lmqZ3TdP05a21b2utPZYve8KWmabpl7XWbm+vjxbyE621X94VPdM0fX07sHp8+PDf\nv2mapuunA35pO5CZ/90V1729tfZ/tdb+wm63+57B3++ZpunGw/2Dfn1r7Xc3RMOcpunrD+1c17XW\n/mxr7eHdbvcPjuYTwhaYpunioYXxHYd94te11n57O1x7TtP0lYfzZmutfcXhvDqdRt5tYW4+VAl9\nV2vtX1wZqS+EveMqa9hf0w62Dejvlo+11n5PO1CP98+eZA171fwLc+aXH5b7F7QDYcJbp2n6smOU\nI7R84bMXHO5g/kT/rx3IVT+/2+2eLmbxvtbaj03T9Gpr7f9urX2qHexh0Pm21tpXtYOIJ3+jtfZ7\nd7tdFD4hHPBH2oG96g+1gzCyr7XW/shh//umdvAF6vPtYJPlo6Fdf3M7iKz3w2svutvtfq619pta\na/9KO9iP4C+31r4FXyj9R+1LctinD8/719ZeJ4Q9o//aeIU941BB88dba397mqaXW2v/U2vtu3a7\n3f9+eMpvawcbt77cDvb6+VO73e57W53f1Vq7u7X2HWL3+mBr7SOH+f/nrbVvPjKP/oHW2jPtYN+t\nW1v6atg2u3ZgsXqkHcyPf7a19u/tdrv/5fDvn2oHc+nt7eBHjNdaa3eeRt6Fufk724EV+idoSznm\nfYZw3rE17LNH3i2/2Fp7nkqedrI17FL+S3PmXz4s629vrf3hw3QiSB+T6UsBLkIIIYQQQgghhBDC\nFojCJ4QQQgghhBBCCGFj5AufEEIIIYQQQgghhI2RL3xCCCGEEEIIIYQQNka+8AkhhBBCCCGEEELY\nGG85y4t9/dd//eIO0b/gF3zpO6h/9s/+2Zzm5tJf/OIXr/o5RnYcnXuteOtb3zpMk5//+Z+/ah68\nZ6a/7Mu+FImOdcH7PglL5ap8zsr+lrccv5kx/9O61w7LeC34yEc+Ugoxeh6YpmluVNddd918/NKl\nS3P6hhtuGH72537u55jPnH7729/eWmvt8uXL87ELFy4M8+OzePbZZ+f0U089Naefe+65Of3iiy/O\n6c9//vNzmu3lK7/yK4dp9k3rVz0f5mdpXp91wXNYLyzLl3/5l89p6yc/+7M/O6dZT3Z8lN/b3va2\n4TW/4iu+Yk7353W1cvE+XnvttTn98stfCpj00ksvzelXX311Tr/wwgtzms+Y9D7Ovs5nxOvbeMDj\nX/VVXzWnea8PPPDA3vTNn/mZnxnOm7wfG3tZF2zfvU5tfuTn7JzKnMTjFnF57bg+aiOV+Yv1wrIw\nfZIgFvbZSh2swcrL52TPg32Zz2/N/M/rsCy2XrPny3P42XvuuWdv+ibnzRC2zm6325u++a3f+q1z\n3/zCF77QRml7B7A5tMOxk2mOrzbW2jrPxnWb2487h1XmuNFa4Wja5hsrr80JVvbR3GbXtLJbudbW\nAT9r76R8rjw+aj+WH9vmUl0cPf7DP/zDi30zCp8QQgghhBBCCCGEjZEvfEIIIYQQQgghhBA2xpla\nutbK5ypS4KVzzSJmULJmmMS9IvtaI0M3aXwFkw1WLCpkzXUpzVuyyhzFbCOsA8rd7LOWDzmulYsW\nCnJcO9x5gvdm1kSzKZrlZlRf1kZMGmlp2qJMqmmS14otaAnr3xXbylpbR+X+RmMM69/kxbRu0f5k\nMl6zapoFjGmWh+lRO7Axs5ImvA7LuE/YHGbjzhoLzVrJs81Jlra2fhrWJhvH1875J7FxVaT0o3td\na3tbW8a159t9jCxblbLbOsosCZV1VwghnCY2HvEdb/S+x2P2Tsf8uPZYO9bZ3ErWzKdr338q9qvK\nu/3aOWmUJ+v3JLYs+2zlPvjs7R1mycZl67jK8Up5jSh8QgghhBBCCCGEEDZGvvAJIYQQQgghhBBC\n2BhvmKWLUv9KpBCT3nUsUlBlV3OjEl3qrKKArbWeVORulKOx/ip5jspT2R3d6p31aLud03Jiu5bz\nPpZ2UDdpulnH7BlswdJl8lPauBjpidjO8r19WRQtk8XaczNLEPNh/mYtquys39ss64J5s51ZtKTK\nPdGaxv7ICFzWvqwv9fxZLosMxj7F52tjpcliWV6zevFa73znO+f0yD5mljKWxZ4dMVtbeD0Vi1zl\ns5WIXSdhJGO2+aAS0eok7aJifVv6XMUGulYaX4l8QsxmMBqj10bjImvtdiGEcJrYerESaWqJypqv\n8u552hGJ17LWCr12LD+uRWmtpcvyXnt9+6xtGcDn3c+3PMzGxTW1rWnWEoVPCCGEEEIIIYQQwsbI\nFz4hhBBCCCGEEEIIG+NMNe7XXXfdnKYNhJYPHqedZEm+b1YKYnKwSvQWKyMxCwmvtWSdqkRhsWsS\nltcwqwRZspPYfZqNy56B2bJMtme73tvO5pTHjf5ekQras9tChBGzEFUiqbC/sY56mm3xc5/73Jxm\nP2IebAsVK4NFq2J5zRq21GcrMl/WXSVaINuutWMef+2114Z52rPpn6WF6u1vf/ucpr2LYyyPW9nN\nksfyMh8bPyziXX8GlUhtFj2Cx3nf+xqlay0VeXWvr9OSjo+snHbNk7JkLbJoK28Ua+p4yabZWs1+\nTayeKnaspbLb3ytt8I22LYQQtou933D8rERcHkVlqtifLTJqJWJrZQ5dG7FrjQXK1nmVqJsnsW4v\nzUkniVZVsU4vRai82rVsfbnG0mVpK8va9U1m3BBCCCGEEEIIIYSNkS98QgghhBBCCCGEEDbGmVq6\nrr/++jn9yiuvzGlaPmhfsEgtI9nT2l3CKd0yOw+PW/ok9DLbbu7ErEoWlciw+zMJYcVaseaalKCZ\nvLxyr0s7oh9Nj2SGdh2zB5rcbwvRf8ySw8hN73jHO+b0msgyfOZm1zIrltmcLGIYnxHvw3bT5zmj\nSApmDzEbW8XuybKY7NgsdlZPo3uipYvPziJ20d5lMl7rg1Yu5kkYpYv0z5rVzWTSxNqJWda2TCVC\n4ggb69ZKuk/LxjWaH6xc1l/WRro6CSb57+WsyPEr0UZJJWKY5VmxdI3WK6Qitz+JBSyEEE6K2b9t\nbBrZsbjG4HqOediWJDbGr32POMkcspQf17Rrx++1NqM10b7s/aHCaUXpsrWxvYeOokJXtoeovNeu\nXV9F4RNCCCGEEEIIIYSwMfKFTwghhBBCCCGEEMLGeMOidFmUFkKpF60SI+mb2YbWRqKqSL0tUoxF\nszEp15rrkIrtjPXL+65E7zJZokX3GZXL6t1kg1bvlWdj900YHarL5iyaEMtlz5f3dx4iwZwUWmxo\ng2GUI/ZfkxiyXno9Vmx8xNqRPVu2r4qNi23XInb1Z81jZoE0yxqx+6hIZN/97ncPzzdZca8DPjum\nrV5snOI9sQ4s+pod53UvXbrURozqvRKly9Jm39sn1s4fFZn40jxndrmK1cv6+FoJ+pJNzP7Oslci\nUa21d1UikizJxy26paXtudv9mY3L5uWKdXUUHc3KVbFKbIHv+77vm9MvvPDCMG3jNMd1zrl9fqIl\ntzLWVda6xGwmZqmu9J+l6JaV/mjtcm3/rbTB0dYAlfFobfTStRw36lElIh+x9Qq33Hj11VfL1z9P\nmPWGfdDmjaUIr1xLsJ+O1mFH82BZbP1Vsf8YS2vKk2x/YuPK2jJa/mssXZX3rpPMrZW5jWvd559/\nfk7zHbK3icq2JWw/9k5qVq8K252JQwghhBBCCCGEEN6k5AufEEIIIYQQQgghhI1xppauixcvzmnu\nRk2LBWVMzzzzzJympYtSuS4xo+SpYt2qRL5ZigzWmlvJyGlHBzGJHetlrayedWCyREb66TJGi8hj\n8mKrR3s2dq9mOaHEjm1mZEthG+R1KLM0e8RxbXrnlQsXLszpm266aU4zsh4tXQbrqPdJ1rNFTWKd\nsy9bpAOeQyx6m8nqeXwkr2UebEPsCxXbYSXSlO2+T7udtUfeU68z1h3r3WxsJiPn/fFZsn8xzWfD\nqIssw5133jm8Vq8Pu8+K3cDGGD7ffcXu02wFS7aoSsSHk0TasvKujZ41KsNae5ndB9u0lX2pLEeP\nW732tmyWK7NPMj8b+2wssePkuNa0Cux3tkbagu2L98Z75rr35ptvntOcT2kL6fOiRXOsWJWsTVUi\nFJld2a41eqaVMaNiL6ycU7mu3cdoPjFLaMUuVan3ik3OrmXr3n6OXdOiGNp7E9cc+2qFNqzObRuM\npXZnFq01WwccZY3Nycp1NP+ld0+zwtvaYm1krkpfWooItnb7BNtmhe3eIn9ZWVg3L7744pzmWpfP\nY7T9ifVTeycmFTupsf+zbAghhBBCCCGEEEK4gnzhE0IIIYQQQgghhLAxztTSRasIo7dQumQWCloG\nRjJ9s2hVLFQm8SRLEu2jx42TyOOPe/2KnJWSQ8qLacPg8S5ToyyZNhfbfd7ksiwjJfYmfTNp33PP\nPTenKbcbXcssXWaTq8gm95V77713Tr/rXe+a04ymRGk6+wPriP261zPrjXlwPOA5FhnMon2ZHdHs\nPyavHbVZGw8o37S2WLGK8hyTqLI+Kpau/jzMMmdRr8x6Qfkr0+w/FfsJy0ML4YhKxCGzJ/D6nDcq\nkSHPO5W5rWIt6scrFg+TX1dk70sS7aPHj2vpqlCxM1cic1Qi6KxZj5hlkdexiJZm1bBnYPJ5jjFL\n85k9U5sfbazeghWa6yPOfbxPi5bIKF1cW/Vx2Kwf1mcrlhQqE5oAACAASURBVPe1kdyMJavf2rVw\npR1V8rdxqBIlqd93xWJSsXSdVoQgO3+N3dLquhKN8TS2oXijsfrkmFmxm46scxybOQbYFhe2/rI2\nXbEAms13dL5tQcDr2NYLlbZYYW20sX6+WZ4rY1zFrlW5Jz5jvgcQjis9H3vftb7Jercy2nM39v9N\nNYQQQgghhBBCCCFcwZkqfCzGfOXbV36TNfrmzb4ptW9t7VtWpvnrMH/NrnxbW6Hfa+VX0AqVjavt\nlxQ+G1NJ8HjfzJdqECp8+O02v6m0/OzbT/ul6qWXXhqml37Rbu1L39CyjGs3A7NfX/eVb/zGb5zT\n/BXytttum9M33HDDnObzoqrq1VdfndO9zvn8mQd/4ST81nxJ2deaPwv71dJ+MRn1a3vm1l5ss1Qb\nJ6zdV9rgUv628V5lE2T7JcUUO/aLBWFdWx0s5bFmA8uj7Kui4CSKGZtb+zkVtYqV5bSUjcdVfZyW\novYk6gKrP1uP9D629hc7Wy9Z/7VneZKNy/t92HXWtqUtYJt52lw12lz/6PHedqwNVfpdRWlicCy1\n+a+ilhvlsXaTUbJ2TWtzRWUT847N7Yap2dZS2Yx7VB+mBCT2DCoqiX2Ca0fCeuNak2tXwneckUqY\nio+XX355TjOADJ8L65NKGnuXsvcxU1vbhsT9Xq1ctmk3y0hMDWPvyhwHTX1ufbPnae8DvCc+UwsA\nY3Vt7/+mcq+Mp/18lpFlN8cB653XYXuzNm7sZ08OIYQQQgghhBBCCEq+8AkhhBBCCCGEEELYGGdq\n6aL8yGRlthGoWbp62mSdFcsVr8m0bQZrUjLbeNasJWbbGGEbbdm9korszCxdJkHucjPK4WjX4XFu\nSFjZYNdkuXw23JCZMkqTH77yyiuvK4PJ6k1uSCr2uX3iAx/4wJzmPd98881zutv4Wruy7T7//PNz\nmvXc2yzrmZv1UjbK50yLHscM29CMbeeFF14Ynl/ZtHBkcazYPUz2Xdkc2WxJ7O+sg4odracrGwJW\nNu60caoyzlr9mi1ktMFdZZNLclobC54XlmT8RzmuRXitdazCWptz5VqjcaWSh22kTCqbwVYsaByf\nRtZlzmWUoNvYx3UG5z6OJZxnOf9yLcJ+Z2Po0ibdttEnqdiItrCBs9lwK5v6kqV+XdnYvDJmVjaM\ntedP1gQrsTVcxf5k1qK1bces06N5zuYM227C7mPtuFn5rI2nvZyVjWmtvFuzYfIZ2bvGyPLU2pVt\nmuPqqI7svYRrUZ5DODZzvOd1eA7hnGDpkd2Ma3Sea9fke59hli7WO9/NmD/r14IQ9HLyvYt/533y\nfYT3x/cNblXBdxKWl/dh31dwDuWcO9r+geW1tYjVCzF7WYUofEIIIYQQQgghhBA2Rr7wCSGEEEII\nIYQQQtgYZ2rpopSMO6Izyg9lcJRpmYSypytySJM7mjXBoguYzPO48vWKJNWi2pic1mSLdq8m56Ss\nbLSjPCMt3XTTTa/7e2utXXfddXPapJV2fZNcMh/eE6V3lMeN5IRsX4RtzSw0rDuWkdffJy5dujSn\nec98vnyOJhdme+lyQ0oj+XfKIU1+a/YBykz5LCxCgDGKusDPWh4mkze5dMVaapEcLCLZkty9Mg4S\n3mvFQmrXr4yhPGfJQmBWCbsPO752fN5X3uioKqcV4cWsvUt52vOv2CTss9buLE+btzqce7gu4nHO\nJbQtP/jgg3Oa8xol65x/bf7ncc6VNhf3z54ksttaq9N5p2JdszXE0tqtYpuydmllWRP59mqYVXdk\n+1trFTLrb2Werazrl65bsYQaZtEmlchfNv/bWmBU7+S4VsKr5XneqYz3XP+ZhWa0LqpY5Oy5cd3L\na3J9zfGY47rdBzEL5dF7aM3HALYL5rFk9z1aLt6rbWtgdbn0bl1ZC9rYa8+j8r7H+uNz4rsS66PP\n75zPzVbK/HhNriEq0XyNKHxCCCGEEEIIIYQQNka+8AkhhBBCCCGEEELYGGeqcaeNi9Jli05DuRkl\nTaNIT2bNMDlzJXIBsV3Imb/ZTJaiFJhdzKhIoa1OjUoEk5GNivdsUUIoSeQ5/GxlB3Oz/bBtUJ5n\nUYz6s7FoSbxOJeoBqexofx5hhDXCehtZE1q78lmM+o/1XYtcYBFuTA7P/mDP36xIxihih8lNTdLL\na5p0luezntgGKfUlrOuRrN3asY1xtI0Qs9LZOGiwDihvHUlnzRZk0VYsal5sXNfmc9cqnzeCyty3\ndo4mI5uH9RebhxjB5ZFHHpnTlJGzD5hMnOdUZPVktNawtUhF+r8FS5dFlbVxymwTFavXKA9b51mE\nGWL2vspYvmTpsnMt6ikxK4yt5+xapGKdGp1j9Wtzq+XNfse+bHMo5y3OuUxzbTSq14oVy9a3dq9b\nYBSNtbUr302WrL2V6J/WdjlmX7x4cU4zWhTX4xali+/TXLsx0iPvr7cvW3ebzcjGG7YvXofrVUb2\n5T3Rcsx6sojd/Tivz+8QbMxk2Xl9bj/Cere6tudtUbp4zsjSZdHA7XsDjhknYX9XaSGEEEIIIYQQ\nQghhSL7wCSGEEEIIIYQQQtgYZ6p3/8xnPjOnX3zxxTlNiTKP0wpEmdhIYmgS00qEGZO2GmYZYLQN\nyrfM9rQUCcgkunYOodSMkTxsF3KWy+Sq/GzPk/dm0bIo96tIvc3W9/jjj8/pj370o3P64x//+Jxm\nxDeWgdHfuvyRFhrKI03iv2ShOXp8nzBZtkmazXIzsslZNC6m7foVqbvZlSwfi8ozktvbeGBR2mwc\nqkQIrERiqeTZ0+w7FduZRaezqFs2Ttj4a5Lx0bXWRgIyKlaVfaISkea83udaC89Z3UfFxlWxYJld\nlfNQn3Oef/75+dhTTz01p59++uk5zbUQj3/kIx+Z0zfffPOcZqRFluXGG2+c0xyfLfpLZRxa83fr\ng/tq4yJmd6jYrmz87nXEulqyOrQ2bmetXWl9qFiOzbZRmZeX1j9my2K75HqRNgnaLbjutPVzxfK7\nFMmTn2Pa1jH2rC3iHt8Z+FnWh0UCoi2mr8crc4LNydZ+11pYzyMVK6VZ8EbHK1GbiT1Pjtl33333\nnKb9yKKH8Z3G5gqWs9uCbOsAps1axHY8eh9s7Uq71O233z6nb7nlljnN+2N/t7Gtl512NaYrNlDa\n51iuW2+9dVguftbmf/sugGXv75bs92bpInxOHCfs+hX28+00hBBCCCGEEEIIISj5wieEEEIIIYQQ\nQghhY5yppYsSLLM/mZRwtNt4a1+SQ9nu/2vliCZ9NOtFRfrIHbb52W51sSheZteya1JSxs+ybsyq\nwTJYhABac7rM0CS3vA7vifdvEQcI645t5oknnpjTTz755JymNYtSOcqaezscRUy7Wtqex1Kkh32g\nYjMy+atJwztmJ1qStF/tmpa2qHwVCfqobDYGsL1WZPpWp5ZnpU2Z9H4UYYz90e7JLIuVCEUmLbW6\n5ljC/Hu6YlGyeyLn1d60hkqkseNauirtzCTH9myt/5os2sprdqnj2mZtrrS1AyXVXKOw7XIO4xzD\ne+K658EHH2yttXbffffNx37sx35sTlOmz/w+9alPzWlKw++66645/cEPfnBOX758eU7bvY7G6taW\nn7fZY9dGfdrCvEms3qz+l9q02W2YNls601znPPvss3Oa7ZJYuzBG2wSw7Lxn9hcep22F2zdw/cc0\n15qVyJxrIsVVInNa1E2uBZ555pk5PdpS4Ohx5sl6os3ExsRe9lEk3aNULF22ttgnbL1esZ5aVObe\nl21bgNG7aWtXPhfa8m677bY5feedd85pPnO2bz5T9gH2JfaTke3JbPxms6+8D/A9kFGvOD9xTqLN\nuDJv9PHsscceayNsWwU+J7M/097FZ1N5xoTnsC/3uqHtjc/IbKC2jiJr+2YUPiGEEEIIIYQQQggb\nI1/4hBBCCCGEEEIIIWyMM7V00ZJDySmlUyZfM4tSP8dsVsQkjpTbmYzL7D+V/CnHGsnmKvJQi/ph\nO/tTYkcscg/lZpS1MR+me4QARgrg382+wfo1C4tFjDA5q8lPl/KxKFEmZ7RID1uIPLI2ak5Fgt+f\nkX3OjlesJSZxZN+o2Hzs2fX2YjJX9jWTxVZk5JWxqiKvHslJK5G2mJ9FLKlY7+yerF8t2XIqdlpi\nticrYzjgJFaaitWLWLurRMa0CIFL2P2ZRNv6zGjNcTQfjj2MmvLAAw/M6X/yT/5Ja621H//xH5+P\nffjDHx7mx/mUZaEcnZFHrr/++jltkUE555rEfInK3LfWoruvVKL1VCxwo3ZqdnKLssN2zLU2o5sy\nIi7tHhVLO7H+0+/JthGwCFy0eJjdgVSipLKurd5Hbbky39qWBax33gej8j388MNzms+AZWffrETv\n6mtsu+eTROaqjM/nkbXry8q6rB+vvOsxzfF49B7V2pXjN49blGO+Q4+i47Y2fm+kVZhzllk5K5Z+\nvuPRkmkRu3jc+hLp8yktkPYuyb7DNOuXljke57Ox+66sRXhOf/Yso0WFrkTmOlHU2mN/MoQQQggh\nhBBCCCGcS/KFTwghhBBCCCGEEMLGeMOidJldyWT/tvv+aGd9kxybhYfXN6uQXZ/YdU02OYpIY/Iu\nk+ERs6ZRqmcRRighpNyOUttR2ixfo8g7rXn0n4oEmsf5zFg3jEJhUbo6Zpuxc6w9VqLonHcqMsHj\n2tgqktBKdKtKGc2WtDZiw1LeJrO1fl+xMphMvWK3GLVfa6O8D5OL2/PlZysSYHseZPSMK3aPSqQ2\nezb7xFlFM6rUeeV5WsQuYn3D7Blr7tvOtfmmErXOrJ2cizlfM3LkZz/72Tnd7V2MMsk5mRJ0ys4p\nh7/33nuH599yyy1zmhFJLAoZ74l92c5fwvpjJUrjvlqhSWUMsvNHliOrE1s7M805g+2SlgjajGwr\nA1uvLVmtbM1ZiaxofZBzrlkvzbpViXLT78kiBZmtw8YAvu+wrvkMeI6tI7k2r0T77OzrfHda2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okCObQMUmYVSi5tn5pGLvZtl6W2Z/ZB+krfIzn/nMnGYEPc5PZl+kzYl9+dKlS3Pa7CeUd1Om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hp7EPZRPpP1znfmczjHmWMn9+yE453r+Z133rlPczyyDcacZ26cHPeEdce5pPM95LKzVWbM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LbGse0Y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\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1HoNASxO/q/Z+x/0yvwdzD8dosNwD23pn48vqxtrA1o1eN6wX2rtYF2+88cY+zUhe9l2O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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7834db6128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['figure.figsize'] = (20.0, 20.0)\n",
    "f, ax = plt.subplots(nrows=5, ncols=5)\n",
    "\n",
    "im_samples = []\n",
    "\n",
    "for row in range(5):\n",
    "    for i, j in enumerate(np.sort(np.random.randint(0, train_labels.shape[0], size=5))):\n",
    "        im = train_dataset[j].reshape((64, 64, 1))\n",
    "        house_num = ''\n",
    "        for k in np.arange(train_labels[j,0]):\n",
    "            house_num += str(train_labels[j,k+1])\n",
    "        house_num += \"--\" + str(j)\n",
    "        im_samples.extend([j])\n",
    "        ax[row, i].axis('off')\n",
    "        ax[row, i].set_title(house_num, loc='center')\n",
    "        ax[row, i].imshow(im[:,:,0], cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class Net(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(Net, self).__init__()\n",
    "        self.conv1 = nn.Conv2d(1, 20, 3, padding=(1, 1))\n",
    "        self.bn1 = nn.BatchNorm2d(20)\n",
    "        self.conv2 = nn.Conv2d(20, 40, 3, padding=(1, 1))\n",
    "        self.bn2 = nn.BatchNorm2d(40)\n",
    "        self.conv3 = nn.Conv2d(40, 80, 3, padding=(1, 1))\n",
    "        self.bn3 = nn.BatchNorm2d(80)\n",
    "        self.conv4 = nn.Conv2d(80, 120, 3, padding=(1, 1))\n",
    "        self.bn4 = nn.BatchNorm2d(120)\n",
    "        self.conv5 = nn.Conv2d(120, 160, 3, padding=(1, 1))\n",
    "        self.bn5 = nn.BatchNorm2d(160)\n",
    "        self.conv6 = nn.Conv2d(160, 200, 3, padding=(1, 1))\n",
    "        self.bn6 = nn.BatchNorm2d(200)\n",
    "        self.conv7 = nn.Conv2d(200, 240, 3, padding=(1, 1))\n",
    "        self.bn7 = nn.BatchNorm2d(240)\n",
    "        self.pool = nn.MaxPool2d(2, 2)\n",
    "        self.FC = nn.Linear(960, 1080)\n",
    "        self.bn8 = nn.BatchNorm1d(1080)\n",
    "        self.digitlength = nn.Linear(1080, 7)\n",
    "        self.digit1 = nn.Linear(1080, 10)\n",
    "        self.digit2 = nn.Linear(1080, 10)\n",
    "        self.digit3 = nn.Linear(1080, 10)\n",
    "        self.digit4 = nn.Linear(1080, 10)\n",
    "        self.digit5 = nn.Linear(1080, 10)\n",
    "        \n",
    "        for m in self.modules():\n",
    "            if isinstance(m, nn.Conv2d):\n",
    "                init.kaiming_normal(m.weight)\n",
    "                m.bias.data.zero_()\n",
    "            elif isinstance(m, nn.Linear):\n",
    "                init.kaiming_normal(m.weight)\n",
    "                m.bias.data.zero_()\n",
    "    \n",
    "    def forward(self, x):\n",
    "        x = self.bn1(F.relu(self.conv1(x)))\n",
    "        x = self.pool(self.bn2(F.relu(self.conv2(x))))\n",
    "        x = self.bn3(F.relu(self.conv3(x)))\n",
    "        x = self.pool(self.bn4(F.relu(self.conv4(x))))\n",
    "        x = self.pool(self.bn5(F.relu(self.conv5(x))))\n",
    "        x = self.pool(self.bn6(F.relu(self.conv6(x))))\n",
    "        x = self.pool(self.bn7(F.relu(self.conv7(x))))\n",
    "        x = x.view(-1, 960)\n",
    "        x = self.bn8(F.relu(self.FC(x)))\n",
    "        yl = self.digitlength(x)\n",
    "        y1 = self.digit1(x)\n",
    "        y2 = self.digit2(x)\n",
    "        y3 = self.digit3(x)\n",
    "        y4 = self.digit4(x)\n",
    "        y5 = self.digit5(x)\n",
    "        return [yl, y1, y2, y3, y4, y5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!\n"
     ]
    }
   ],
   "source": [
    "net = Net()\n",
    "net.cuda()\n",
    "print(\"!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "None\n"
     ]
    }
   ],
   "source": [
    "print(list(net.parameters())[0][0].grad)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for param in net.parameters():\n",
    "    if(param.grad is not None):\n",
    "        print(param)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.FloatTensor torch.Size([750, 1, 64, 64])\n",
      "torch.LongTensor torch.Size([750, 6])\n"
     ]
    }
   ],
   "source": [
    "data_tensor = torch.from_numpy(train_dataset)\n",
    "target_tensor = torch.from_numpy(train_labels).type(torch.LongTensor)\n",
    "print(data_tensor.type(), data_tensor.size())\n",
    "print(target_tensor.type(), target_tensor.size())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "objective = nn.CrossEntropyLoss()\n",
    "optimizer = optim.Adam(net.parameters())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "750\n",
      "11\n"
     ]
    }
   ],
   "source": [
    "num_epochs = 100\n",
    "batch_size = 64\n",
    "num_train = data_tensor.size()[0]\n",
    "print(num_train)\n",
    "iter_per_epoch = num_train // batch_size\n",
    "print_every = 3\n",
    "print(iter_per_epoch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "epoch_losses = {i:[] for i in range(num_epochs)}\n",
    "loss_history = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Net (\n",
       "  (conv1): Conv2d(1, 20, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "  (bn1): BatchNorm2d(20, eps=1e-05, momentum=0.1, affine=True)\n",
       "  (conv2): Conv2d(20, 40, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "  (bn2): BatchNorm2d(40, eps=1e-05, momentum=0.1, affine=True)\n",
       "  (conv3): Conv2d(40, 80, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "  (bn3): BatchNorm2d(80, eps=1e-05, momentum=0.1, affine=True)\n",
       "  (conv4): Conv2d(80, 120, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "  (bn4): BatchNorm2d(120, eps=1e-05, momentum=0.1, affine=True)\n",
       "  (conv5): Conv2d(120, 160, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "  (bn5): BatchNorm2d(160, eps=1e-05, momentum=0.1, affine=True)\n",
       "  (conv6): Conv2d(160, 200, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "  (bn6): BatchNorm2d(200, eps=1e-05, momentum=0.1, affine=True)\n",
       "  (conv7): Conv2d(200, 240, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "  (bn7): BatchNorm2d(240, eps=1e-05, momentum=0.1, affine=True)\n",
       "  (pool): MaxPool2d (size=(2, 2), stride=(2, 2), dilation=(1, 1))\n",
       "  (FC): Linear (960 -> 1080)\n",
       "  (bn8): BatchNorm1d(1080, eps=1e-05, momentum=0.1, affine=True)\n",
       "  (digitlength): Linear (1080 -> 7)\n",
       "  (digit1): Linear (1080 -> 10)\n",
       "  (digit2): Linear (1080 -> 10)\n",
       "  (digit3): Linear (1080 -> 10)\n",
       "  (digit4): Linear (1080 -> 10)\n",
       "  (digit5): Linear (1080 -> 10)\n",
       ")"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "net.train()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.029112156480550766\n",
      "loss3d :  0.014649080112576485 loss2d :  0.011504385620355606 loss1d :  0.00295869167894125\n",
      "Iteration :  4  /  11\n",
      "loss :  0.036482248455286026\n",
      "loss3d :  0.02013366110622883 loss2d :  0.01352018117904663 loss1d :  0.0028284071013331413\n",
      "Iteration :  7  /  11\n",
      "loss :  0.03918202966451645\n",
      "loss3d :  0.02373810112476349 loss2d :  0.013007529079914093 loss1d :  0.002436399459838867\n",
      "Iteration :  10  /  11\n",
      "loss :  0.03289094567298889\n",
      "loss3d :  0.01590704917907715 loss2d :  0.013688473962247372 loss1d :  0.003295421600341797\n",
      "time taken :  34.66706562042236\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 1/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.036058127880096436\n",
      "loss3d :  0.0173178743571043 loss2d :  0.01639036275446415 loss1d :  0.0023498916998505592\n",
      "Iteration :  4  /  11\n",
      "loss :  0.027174614369869232\n",
      "loss3d :  0.011958980932831764 loss2d :  0.009989547543227673 loss1d :  0.005226085893809795\n",
      "Iteration :  7  /  11\n",
      "loss :  0.03400509059429169\n",
      "loss3d :  0.015644822269678116 loss2d :  0.015808312222361565 loss1d :  0.002551959129050374\n",
      "Iteration :  10  /  11\n",
      "loss :  0.028371158987283707\n",
      "loss3d :  0.015369726344943047 loss2d :  0.011585021391510963 loss1d :  0.0014164106687530875\n",
      "time taken :  34.64530539512634\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 2/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.02561701275408268\n",
      "loss3d :  0.01350166741758585 loss2d :  0.009900117293000221 loss1d :  0.002215226413682103\n",
      "Iteration :  4  /  11\n",
      "loss :  0.04842358082532883\n",
      "loss3d :  0.019615331664681435 loss2d :  0.017226792871952057 loss1d :  0.011581458151340485\n",
      "Iteration :  7  /  11\n",
      "loss :  0.023471077904105186\n",
      "loss3d :  0.009861230850219727 loss2d :  0.0103868143633008 loss1d :  0.0032230340875685215\n",
      "Iteration :  10  /  11\n",
      "loss :  0.03978898376226425\n",
      "loss3d :  0.02516239508986473 loss2d :  0.01352455373853445 loss1d :  0.0011020342353731394\n",
      "time taken :  34.76257252693176\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 3/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.032834168523550034\n",
      "loss3d :  0.019537312909960747 loss2d :  0.012667093425989151 loss1d :  0.0006297656218521297\n",
      "Iteration :  4  /  11\n",
      "loss :  0.029164006933569908\n",
      "loss3d :  0.01681707240641117 loss2d :  0.010711312294006348 loss1d :  0.0016356229316443205\n",
      "Iteration :  7  /  11\n",
      "loss :  0.021548788994550705\n",
      "loss3d :  0.009943680837750435 loss2d :  0.007450681179761887 loss1d :  0.0041544269770383835\n",
      "Iteration :  10  /  11\n",
      "loss :  0.021265285089612007\n",
      "loss3d :  0.011685640551149845 loss2d :  0.007601764984428883 loss1d :  0.001977879088371992\n",
      "time taken :  35.12862849235535\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 4/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.022777587175369263\n",
      "loss3d :  0.010214973241090775 loss2d :  0.010902919806540012 loss1d :  0.0016596944769844413\n",
      "Iteration :  4  /  11\n",
      "loss :  0.027156416326761246\n",
      "loss3d :  0.01618446595966816 loss2d :  0.008328041061758995 loss1d :  0.002643909538164735\n",
      "Iteration :  7  /  11\n",
      "loss :  0.0190771222114563\n",
      "loss3d :  0.009549111127853394 loss2d :  0.00737003656104207 loss1d :  0.0021579740568995476\n",
      "Iteration :  10  /  11\n",
      "loss :  0.023969467729330063\n",
      "loss3d :  0.01127343438565731 loss2d :  0.011008620262145996 loss1d :  0.0016874131979420781\n",
      "time taken :  41.76643371582031\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 5/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.018502769991755486\n",
      "loss3d :  0.010832559317350388 loss2d :  0.006705820560455322 loss1d :  0.000964390579611063\n",
      "Iteration :  4  /  11\n",
      "loss :  0.01880449801683426\n",
      "loss3d :  0.008061885833740234 loss2d :  0.009687547571957111 loss1d :  0.0010550649603828788\n",
      "Iteration :  7  /  11\n",
      "loss :  0.020615065470337868\n",
      "loss3d :  0.011992370709776878 loss2d :  0.007604473736137152 loss1d :  0.001018220791593194\n",
      "Iteration :  10  /  11\n",
      "loss :  0.02106759510934353\n",
      "loss3d :  0.009723559021949768 loss2d :  0.009618563577532768 loss1d :  0.001725472859106958\n",
      "time taken :  44.00980234146118\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 6/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.01761205494403839\n",
      "loss3d :  0.00865453202277422 loss2d :  0.008297253400087357 loss1d :  0.0006602704524993896\n",
      "Iteration :  4  /  11\n",
      "loss :  0.01909506320953369\n",
      "loss3d :  0.011029833927750587 loss2d :  0.006965065374970436 loss1d :  0.0011001636739820242\n",
      "Iteration :  7  /  11\n",
      "loss :  0.023621995002031326\n",
      "loss3d :  0.015288131311535835 loss2d :  0.006987627595663071 loss1d :  0.0013462367933243513\n",
      "Iteration :  10  /  11\n",
      "loss :  0.018215129151940346\n",
      "loss3d :  0.009618572890758514 loss2d :  0.007717609405517578 loss1d :  0.0008789471467025578\n",
      "time taken :  46.09221053123474\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 7/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.013969510793685913\n",
      "loss3d :  0.0064811985939741135 loss2d :  0.005569978151470423 loss1d :  0.0019183349795639515\n",
      "Iteration :  4  /  11\n",
      "loss :  0.019633937627077103\n",
      "loss3d :  0.012860591523349285 loss2d :  0.0049322545528411865 loss1d :  0.0018410899210721254\n",
      "Iteration :  7  /  11\n",
      "loss :  0.015269797295331955\n",
      "loss3d :  0.008010189048945904 loss2d :  0.006054289173334837 loss1d :  0.0012053200043737888\n",
      "Iteration :  10  /  11\n",
      "loss :  0.01699678972363472\n",
      "loss3d :  0.007757234387099743 loss2d :  0.0069969892501831055 loss1d :  0.002242565155029297\n",
      "time taken :  48.38093113899231\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 8/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.0170399509370327\n",
      "loss3d :  0.008762722834944725 loss2d :  0.006311078555881977 loss1d :  0.0019661502446979284\n",
      "Iteration :  4  /  11\n",
      "loss :  0.015867069363594055\n",
      "loss3d :  0.00878845527768135 loss2d :  0.005835583433508873 loss1d :  0.001243031583726406\n",
      "Iteration :  7  /  11\n",
      "loss :  0.017387378960847855\n",
      "loss3d :  0.007286095526069403 loss2d :  0.009135901927947998 loss1d :  0.0009653806919232011\n",
      "Iteration :  10  /  11\n",
      "loss :  0.015147995203733444\n",
      "loss3d :  0.008767982944846153 loss2d :  0.005651431158185005 loss1d :  0.0007285806350409985\n",
      "time taken :  46.76351881027222\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 9/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.014521945267915726\n",
      "loss3d :  0.007614198140799999 loss2d :  0.0050101918168365955 loss1d :  0.0018975551938638091\n",
      "Iteration :  4  /  11\n",
      "loss :  0.015221163630485535\n",
      "loss3d :  0.008519916795194149 loss2d :  0.005857793614268303 loss1d :  0.0008434534538537264\n",
      "Iteration :  7  /  11\n",
      "loss :  0.016585389152169228\n",
      "loss3d :  0.009760243818163872 loss2d :  0.005529474932700396 loss1d :  0.0012956702848896384\n",
      "Iteration :  10  /  11\n",
      "loss :  0.015985896810889244\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss3d :  0.009071849286556244 loss2d :  0.0045419055968523026 loss1d :  0.0023721412289887667\n",
      "time taken :  45.71832227706909\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 10/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.015617001801729202\n",
      "loss3d :  0.00783503707498312 loss2d :  0.005650096572935581 loss1d :  0.002131868153810501\n",
      "Iteration :  4  /  11\n",
      "loss :  0.01139034889638424\n",
      "loss3d :  0.005664893426001072 loss2d :  0.004510653670877218 loss1d :  0.0012148022651672363\n",
      "Iteration :  7  /  11\n",
      "loss :  0.01768525503575802\n",
      "loss3d :  0.010251430794596672 loss2d :  0.0070406910963356495 loss1d :  0.0003931339015252888\n",
      "Iteration :  10  /  11\n",
      "loss :  0.010039519518613815\n",
      "loss3d :  0.004606366157531738 loss2d :  0.002929789712652564 loss1d :  0.0025033631827682257\n",
      "time taken :  46.74090576171875\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 11/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.010571922175586224\n",
      "loss3d :  0.00489327497780323 loss2d :  0.004418704658746719 loss1d :  0.0012599428882822394\n",
      "Iteration :  4  /  11\n",
      "loss :  0.014181390404701233\n",
      "loss3d :  0.008610322140157223 loss2d :  0.004846466705203056 loss1d :  0.0007246017339639366\n",
      "Iteration :  7  /  11\n",
      "loss :  0.010766967199742794\n",
      "loss3d :  0.005214989185333252 loss2d :  0.004116882104426622 loss1d :  0.001435096375644207\n",
      "Iteration :  10  /  11\n",
      "loss :  0.012726380489766598\n",
      "loss3d :  0.006340113468468189 loss2d :  0.005386753939092159 loss1d :  0.0009995128493756056\n",
      "time taken :  53.663002252578735\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 12/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.011985422112047672\n",
      "loss3d :  0.0052278414368629456 loss2d :  0.00561070442199707 loss1d :  0.0011468762531876564\n",
      "Iteration :  4  /  11\n",
      "loss :  0.011673584580421448\n",
      "loss3d :  0.005848884582519531 loss2d :  0.004745216108858585 loss1d :  0.001079484005458653\n",
      "Iteration :  7  /  11\n",
      "loss :  0.011274877935647964\n",
      "loss3d :  0.005462937988340855 loss2d :  0.00475443946197629 loss1d :  0.00105750048533082\n",
      "Iteration :  10  /  11\n",
      "loss :  0.01234632357954979\n",
      "loss3d :  0.006704081781208515 loss2d :  0.005017585586756468 loss1d :  0.0006246566772460938\n",
      "time taken :  46.98327994346619\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 13/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.021618183702230453\n",
      "loss3d :  0.015478529036045074 loss2d :  0.005475270561873913 loss1d :  0.0006643831729888916\n",
      "Iteration :  4  /  11\n",
      "loss :  0.010179856792092323\n",
      "loss3d :  0.004215061664581299 loss2d :  0.004727581981569529 loss1d :  0.0012372136116027832\n",
      "Iteration :  7  /  11\n",
      "loss :  0.009760415181517601\n",
      "loss3d :  0.004451443441212177 loss2d :  0.004341468680649996 loss1d :  0.0009675025939941406\n",
      "Iteration :  10  /  11\n",
      "loss :  0.012272948399186134\n",
      "loss3d :  0.00710606575012207 loss2d :  0.003943133167922497 loss1d :  0.001223749597556889\n",
      "time taken :  45.93968987464905\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 14/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.015744920819997787\n",
      "loss3d :  0.009332114830613136 loss2d :  0.005045273806899786 loss1d :  0.0013675307855010033\n",
      "Iteration :  4  /  11\n",
      "loss :  0.016679394990205765\n",
      "loss3d :  0.009216376580297947 loss2d :  0.006848424673080444 loss1d :  0.00061459542484954\n",
      "Iteration :  7  /  11\n",
      "loss :  0.012076850049197674\n",
      "loss3d :  0.006059689912945032 loss2d :  0.005304098129272461 loss1d :  0.0007130622980184853\n",
      "Iteration :  10  /  11\n",
      "loss :  0.010481329634785652\n",
      "loss3d :  0.0037416848354041576 loss2d :  0.0036951513029634953 loss1d :  0.0030444939620792866\n",
      "time taken :  46.46403694152832\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 15/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.011092223227024078\n",
      "loss3d :  0.005732922814786434 loss2d :  0.004861935041844845 loss1d :  0.0004973650211468339\n",
      "Iteration :  4  /  11\n",
      "loss :  0.008808864280581474\n",
      "loss3d :  0.0047943987883627415 loss2d :  0.00313207833096385 loss1d :  0.0008823871612548828\n",
      "Iteration :  7  /  11\n",
      "loss :  0.008777251467108727\n",
      "loss3d :  0.0036461493000388145 loss2d :  0.004400825593620539 loss1d :  0.0007302761077880859\n",
      "Iteration :  10  /  11\n",
      "loss :  0.009194857440888882\n",
      "loss3d :  0.004929201677441597 loss2d :  0.003531001741066575 loss1d :  0.0007346543716266751\n",
      "time taken :  47.86466836929321\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 16/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.010130784474313259\n",
      "loss3d :  0.0053054094314575195 loss2d :  0.003596782684326172 loss1d :  0.0012285925913602114\n",
      "Iteration :  4  /  11\n",
      "loss :  0.011659468524158001\n",
      "loss3d :  0.005537009332329035 loss2d :  0.0055780960246920586 loss1d :  0.0005443625850602984\n",
      "Iteration :  7  /  11\n",
      "loss :  0.011548567563295364\n",
      "loss3d :  0.006111939437687397 loss2d :  0.004814130254089832 loss1d :  0.0006224983371794224\n",
      "Iteration :  10  /  11\n",
      "loss :  0.009642002172768116\n",
      "loss3d :  0.004248814191669226 loss2d :  0.004240740090608597 loss1d :  0.0011524473084136844\n",
      "time taken :  47.65708351135254\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 17/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.011083737015724182\n",
      "loss3d :  0.004228206351399422 loss2d :  0.006545458920300007 loss1d :  0.0003100713074672967\n",
      "Iteration :  4  /  11\n",
      "loss :  0.008527789264917374\n",
      "loss3d :  0.004942200146615505 loss2d :  0.0027116606943309307 loss1d :  0.0008739280747249722\n",
      "Iteration :  7  /  11\n",
      "loss :  0.00992013793438673\n",
      "loss3d :  0.005060781259089708 loss2d :  0.003910450730472803 loss1d :  0.0009489059448242188\n",
      "Iteration :  10  /  11\n",
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      "loss3d :  0.003435638267546892 loss2d :  0.0033390955068171024 loss1d :  0.0008761485805734992\n",
      "time taken :  47.34559512138367\n",
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      "Epoch 18/99\n",
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      "time taken :  51.549670934677124\n",
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      "Epoch 19/99\n",
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      "loss :  0.010003700852394104\n",
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      "loss3d :  0.003806504188105464 loss2d :  0.0025800943840295076 loss1d :  0.0008523680735379457\n"
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      "time taken :  48.89442157745361\n",
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      "Epoch 20/99\n",
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      "loss :  0.006672471296042204\n",
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      "time taken :  48.06630492210388\n",
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      "Epoch 21/99\n",
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      "loss :  0.007216854952275753\n",
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      "time taken :  48.624088287353516\n",
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      "Epoch 22/99\n",
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      "loss :  0.00593740027397871\n",
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      "loss3d :  0.0030414192005991936 loss2d :  0.0027070953510701656 loss1d :  0.00048221860197372735\n",
      "time taken :  48.45227098464966\n",
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      "Epoch 23/99\n",
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      "loss :  0.0052113826386630535\n",
      "loss3d :  0.0018966898787766695 loss2d :  0.002389647765085101 loss1d :  0.0009250449948012829\n",
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      "time taken :  48.42343544960022\n",
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      "Epoch 24/99\n",
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      "loss :  0.007921229116618633\n",
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      "loss3d :  0.00688514718785882 loss2d :  0.0028756989631801844 loss1d :  0.0002535581588745117\n",
      "time taken :  48.77754211425781\n",
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      "Epoch 25/99\n",
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      "loss :  0.007478673942387104\n",
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      "time taken :  48.423853635787964\n",
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      "Epoch 29/99\n",
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     ]
    },
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      "Epoch 30/99\n",
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      "time taken :  48.219499826431274\n",
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      "time taken :  51.303499937057495\n",
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      "time taken :  48.43203353881836\n",
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      "Epoch 39/99\n",
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      "time taken :  48.66650080680847\n",
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      "time taken :  49.15477156639099\n",
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      "time taken :  48.700615644454956\n",
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      "Epoch 58/99\n",
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     ]
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      "time taken :  49.649617195129395\n",
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      "time taken :  50.31738471984863\n",
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      "time taken :  49.84651780128479\n",
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     "output_type": "stream",
     "text": [
      "time taken :  50.25066423416138\n",
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      "time taken :  48.74734091758728\n",
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      "time taken :  48.375574350357056\n",
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      "time taken :  48.17167115211487\n",
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      "time taken :  48.39279508590698\n",
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      "time taken :  51.53493309020996\n",
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      "time taken :  48.12635517120361\n",
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      "time taken :  48.51235890388489\n",
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      "Epoch 87/99\n",
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      "time taken :  48.74049711227417\n",
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      "time taken :  48.30777907371521\n",
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      "Iteration :  7  /  11\n",
      "loss :  0.0006075119599699974\n",
      "loss3d :  0.00026934489142149687 loss2d :  0.00029345660004764795 loss1d :  4.4710493966704234e-05\n",
      "Iteration :  10  /  11\n",
      "loss :  0.0006041951710358262\n",
      "loss3d :  0.00041752593824639916 loss2d :  0.00016016709560062736 loss1d :  2.650210626597982e-05\n",
      "time taken :  48.07642865180969\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Epoch 99/99\n",
      "--------------------------------------------------------------------------------------------------------------\n",
      "Iteration :  1  /  11\n",
      "loss :  0.0004967652494087815\n",
      "loss3d :  0.000286102294921875 loss2d :  0.00016706640599295497 loss1d :  4.3596541217993945e-05\n",
      "Iteration :  4  /  11\n",
      "loss :  0.000514709041453898\n",
      "loss3d :  0.0001636806409806013 loss2d :  0.00023040770611260086 loss1d :  0.00012062072346452624\n",
      "Iteration :  7  /  11\n",
      "loss :  0.0004338370345067233\n",
      "loss3d :  0.00020678147848229855 loss2d :  0.00013744831085205078 loss1d :  8.960723789641634e-05\n",
      "Iteration :  10  /  11\n",
      "loss :  0.0007121443632058799\n",
      "loss3d :  0.00038594010402448475 loss2d :  0.00020074844360351562 loss1d :  0.00012545585923362523\n",
      "time taken :  48.9694344997406\n",
      "--------------------------------------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "for epoch in range(num_epochs):  # loop over the dataset multiple times\n",
    "    \n",
    "    print('Epoch {}/{}'.format(epoch, num_epochs - 1))\n",
    "    print('-' * 110)\n",
    "\n",
    "    i = 0\n",
    "    rng_state = torch.get_rng_state()\n",
    "    new_idxs = torch.randperm(num_train)\n",
    "    \n",
    "    t1 = time.time()\n",
    "    for t in range(iter_per_epoch):\n",
    "        batch_idxs = new_idxs[i: i+batch_size]\n",
    "        i += batch_size\n",
    "        X_batch = data_tensor[batch_idxs]\n",
    "        Y_batch = target_tensor[batch_idxs][:,0:4]\n",
    "        lenths = Y_batch[:, 0]\n",
    "        bin3 = []\n",
    "        bin2 = []\n",
    "        bin1 = []\n",
    "        for idx, lenth in enumerate(lenths):\n",
    "            if (lenth == 1):\n",
    "                bin1.append(idx)\n",
    "            elif (lenth == 2):\n",
    "                bin2.append(idx)\n",
    "            elif (lenth == 3):\n",
    "                bin3.append(idx)\n",
    "        \n",
    "\n",
    "        X_batch = Variable(X_batch).cuda()\n",
    "        Y_batch = Variable(Y_batch).cuda()\n",
    "        optimizer.zero_grad()\n",
    "        outputs = net(X_batch)\n",
    "        \n",
    "        if bin3:\n",
    "            idxs = torch.LongTensor(bin3).cuda()\n",
    "            Y = Y_batch[idxs]\n",
    "            lossl = objective(outputs[0][idxs], Y[:, 0])\n",
    "            loss1 = objective(outputs[1][idxs], Y[:, 1])\n",
    "            loss2 = objective(outputs[2][idxs], Y[:, 2])\n",
    "            loss3 = objective(outputs[3][idxs], Y[:, 3])\n",
    "            lossd3 = lossl + loss1 + loss2 + loss3\n",
    "            lossd3.backward(retain_variables=True)\n",
    "            optimizer.step()\n",
    "        \n",
    "        if bin2:\n",
    "            optimizer.zero_grad()\n",
    "            idxs = torch.LongTensor(bin2).cuda()\n",
    "            Y = Y_batch[idxs]\n",
    "            lossl = objective(outputs[0][idxs], Y[:, 0])\n",
    "            loss1 = objective(outputs[1][idxs], Y[:, 1])\n",
    "            loss2 = objective(outputs[2][idxs], Y[:, 2])\n",
    "            lossd2 = lossl + loss1 + loss2\n",
    "            lossd2.backward(retain_variables=True)\n",
    "            optimizer.step()\n",
    "        \n",
    "        if bin1:\n",
    "            optimizer.zero_grad()\n",
    "            idxs = torch.LongTensor(bin1).cuda()\n",
    "            Y = Y_batch[idxs]\n",
    "            lossl = objective(outputs[0][idxs], Y[:, 0])\n",
    "            loss1 = objective(outputs[1][idxs], Y[:, 1])\n",
    "            lossd1 = lossl + loss1\n",
    "            lossd1.backward()\n",
    "            optimizer.step()\n",
    "        \n",
    "        optimizer.step()\n",
    "        final_loss = lossd3 + lossd2 + lossd1\n",
    "        \n",
    "        loss_history.append(final_loss.data[0])\n",
    "        epoch_losses[epoch].append(final_loss.data[0])\n",
    "        \n",
    "        if (t % print_every == 0):\n",
    "            print('Iteration : ', t+1, ' / ', iter_per_epoch)\n",
    "            print('loss : ', final_loss.data[0])\n",
    "            print('loss3d : ', lossd3.data[0], 'loss2d : ', lossd2.data[0], 'loss1d : ', lossd1.data[0])\n",
    "        \n",
    "    t2 = time.time()\n",
    "    print(\"time taken : \", t2-t1)\n",
    "    print('-' * 110)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "f = open(\"c321_overfit_longer.pkl\", \"bw\")\n",
    "torch.save(net.state_dict(), f)\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f7833fe3d68>]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AuBth0T2qzm5DGzmuDQ0AAAC4I2HRY/av3/2heN+HPxkRdx9wLRYCAAAALk1Y9Jj9nR/5\nhfhHP/tbEdEacH1iWFRCpv02tHzyvQAAAADahEWP2fO3VTy/m2hdZhad2oY2Jsf48GsAAACAKYRF\nj9k20Ckh0fbYybuh1Z/dZGg7s+hu7wcAAAC8sAmLHrOqynvtZ5dqHaty3guQAAAAAE4hLHrM2q1i\nJdbZnLobWu5+tu99oY42AAAA4AVKWPSY5dy0j911N7SheyssAgAAAO5CWPSY5Zz3KoNOHXA9vlob\nGgAAAHA3wqLHrMpNq1j5PLUNrcjZgGsAAADgsoRFj1l7CHX5PDkrGkmEclxuWDYAAADwwiQsesxy\n/Y92hdF5bWj9q3LWhAYAAADcjbDoMesEOmXA9YW2MGvvtAYAAABwDmHRY7adK9RtPzt1N7T+gOzO\nve/6ggAAAMALmrDoMaty3ms/O3U3tDHbndbERQAAAMD5hEWPWY7WzKEzd0PrD8ju3FtWBAAAANyB\nsOgx2lb+tNvQup+n369/YD9AAgAAADiFsOgxqmcN9Y6f2oU2li2pLAIAAADuSlj0GDXtZ92KonN3\nQ9srLGrNQwIAAAA4h7DoMSrhUH83s1Pb0A5XFkmLAAAAgPMJix6j/ZBo+3l2ZVE+/BsAAADgVMKi\nx6iuLIq7taGNrc6RBUYAAADAnQiL7kE/0Dm9Da2efrR333N3VgMAAACIEBY9VlU92Hr3u7rjgOuB\nNjRREQAAAHAXwqLHqAl3cuufEZsLJTzbNjRxEQAAAHA+YdFj1N8NrfmtsggAAAC4DsKix6h0m9UT\nh87cDW0sW8oHzgEAAABMISx6nEpY1KsoOntm0d6Aa21oAAAAwN0Iix6j/oDr3Ds+VT8kao5rQwMA\nAADuRlj0GPU3vK/uWlk0NLNIWgQAAADcgbDoMeoPtC4Z0alZUe5VJg09AwAAAOAcwqLHaKgSKOL8\nyqLuvbo7rQEAAACcQ1j0GPUDnabC6NSZReX69r3v+nYAAAAAwqLHqmk724VG5fglKovKp9QIAAAA\nuANh0WNUdjEreU4JiTanVhbVYVPeO3aB3AkAAAB4ARMWPUZVPZi6W1m0qU67z1Ae1Oy0Ji0CAAAA\nzicseoz6M4uqM2cWNTds37v7CQAAAHAOYdGMfu7dz8V3/p+/XP/uBzpn74aWOx+773nvGAAAAMCp\nhEUz+pnfeC5+6G3vrX/nfhtaqSy6xIDr3g5rAAAAAOcQFs0o9yYIVXttaNvPkwdcl8+B62RFAAAA\nwF0Ii+aUu/OI6rCoPn3HmUXtRw20pgEAAACcSlg0oyrnyLm91f1Wf5v76tTd0PL+fKJ+axsAAADA\nOYRFM9ofaN0NifKZbWhDql5rGwAAAMA5hEUzKrlNf1ZRv8Lo1N3Qmutbx7LKIgAAAODuhEUzqvrt\nZr2Up53rnLMjWh74LioCAAAA7uLmvl/gIWt2Pcvxc+96Ln7jDz6+PR7N8WKTc6winXTfwWPSIgAA\nAOAOhEUzareE/Y3vf1vr+PazXUy0qXI8sT7//tFrcQMAAAA4hza0GQ1VELV/51a0c8qooTwQCZVj\n/WcBAAAAnEJYNKOhCqL28Xauc8qOaP1B2WP3BAAAADiVsGhGpcrn0482neP93dAiTt8Rra8ZWSQt\nAgAAAM4nLJpRiW0+9Innu8d7u6RFnLYb2tAw6zywwxoAAADAqYRFMyoBzoc+8Znh863vp7ShNde3\nZh7Vzzz5NgAAAAA1YdGMSnDzoT/uVhZVeX8Y9SmVRYeepQ0NAAAAuAth0YzqsKhXWdQMo27NLDqn\nsqjdhhba0AAAAIC7ExbNqFQOPdefWVQ+27uhnTSzaGDtwA5pAAAAAKcSFs2oHnD9x/3Kov02tHMq\ngrqVRbF3TwAAAIBTCYtmVHKbvcqi3P2MOLGy6MCzZEUAAADAXQiLZjS2G1pTBdQcu/tuaFIiAAAA\n4O6ERTMq8c2nHlXd43UwdN5uaENVRN3vgiMAAADgPMKiGZX5Qf0g6FKVRUP37N8XAAAA4BTCohmV\n/OdR1a8sKp9NqnPazKK8+2y0AymVRQAAAMC5hEUzKpFNPwiqK45ah3t50uH7HsmCREUAAADAuYRF\nMyqh0O2m14aWu+f736can1l08q0AAAAAIkJYNK9daDOlxeyUmUVDK9u7oZ0TPAEAAABECItmVQKc\n2/6A67oN7bzd0NpPaO55xuUAAAAAPcKiGZU5RJv+gOvy2d4N7ZQB17n72b5n/zgAAADAKYRFMxqr\nLKoGKotOaUMbfFbr+mzENQAAAHAmYdGMqpGZRe3KoFXarT1hN7RSR5T3jnSfCwAAAHAqYdGMSii0\nN7Oodf5mtf0juHtlUfu7tAgAAAA4j7BoVrs2tE1vZlGpLIocN+ttadEpA66byqTh2iJREQAAAHAu\nYdGMSv6znwPl+vjNrg/trtvddyuL7nQrAAAA4AVMWDSjsXawJkTKcbPetaGdUlnU+9z7Li0CAAAA\nziQsmtFY/lPCnJwj1mdUFrWvb44NfwcAAAA4hbBoRmOZTTPgOtdtaJuTdkMbuqeZRQAAAMDdCYtm\nNNYO1gy4jnrA9Sm7oQ22odkNDQAAALgAYdGMxjKb0nJW5Rw3q+0fwSm7oR171h1vBQAAALyACYtm\nlMcawkplUWs3tJMGXNfXt1vPhr8DAAAAnEJYNKOxyqJyuMpR74Z2yoDro8+SFQEAAABnEhbNaCwA\nanYzawZcn7Mb2uj5yXcCAAAA6BIWzehYZVHOEes77IbWnVOUB78DAAAAnEJYNKNpA67P3w1t7Fmy\nIgAAAOBcwqIZjQ2argdUR8TNeteGdsYWZt2h1jH4HQAAAOAUwqIZHR9wneNmtf0jOGU3tKE0qLMz\nmtIiAAAA4EzCohmNzg7KzWddWXRGwNNpPRs5DgAAAHAKYdGMxjKb0j52bmWRmUUAAADAXIRFMxof\ncL07H1EPuD6pC2134+792/OLpEUAAADAeYRFM2rPDiqhUPt4lXOs79KG1g6IVBYBAAAAFyAsmlE7\ns1m3w6LdZ1U1IdKd29Ba388JngAAAAAihEWzqkYri5o16xPCoo99+lH8zX/8bHzy+c3efcaGXQMA\nAACcQlg0o3aAc7Ne9c7lbRtaSpHStGqg3/yDT8RP/eofjDxruCUNAAAA4BTCohm1Q5sn1mnvXM4R\nq5RindLENrQ8+mv8DAAAAMB0wqIZtauF2jOLIrZxTpVzpBSxWqXYTCgHOrTEgGsAAADgEoRFj8nN\nar8NLUdE2lUWTQl49pZ05hQ1P06YlQ0AAADQISya0bHKoryrLFqvprWh9QOlHMNTrbM2NAAAAOBM\nwqIZdQdcd8OiKueocsQqRaQ0bTe0Q0OwO/OLZEUAAADAmYRFM2pnNk/staHtKosixXqVJu2GtldZ\nNDKnSFgEAAAAnEtYNKNDbWjb89vKoqm7oR1qL+vOLJIWAQAAAOcRFs3pQBtaXVmUUqwmVhb1syKt\nZwAAAMClCYtm1M5vbvYGXOfIeTuvaGpl0aEl7bBJcAQAAACcS1g0o3aAc7Ne9c5tw6RVSrvd0I7f\nr9+GltsB0YF1AAAAAFMJi2bU2Q2tX1mUc1Q5R4qI1aob/Ey5X0SvK631Y0KREgAAAMAgYdGMDg24\nzrENf1artG1DmxIWHTzXbkOTFgEAAADnERbN6HBlUTSVRZNnFvXb0Ea+n/OyAAAAACEsemz6M4si\nx27A9fm7oXVOjQRHAAAAAKcQFs2oHQA9sU5753Lkk3ZD2xtwPfZdWgQAAACcSVg0o3Zms151/1Pn\n2A6iXqXt3KJJu6EdrCwa3hkNAAAA4BTCohm1K4GGdkPLOccqpViv9ucRDd6vv2QkIFJYBAAAAJxL\nWDSjqlNZtL8bWpUjUmzb0KaERXsDrtvfOzOLpEUAAADAeYRFM2pnNkMziyKaAdf9mUX/3Y+9M77j\nn7+ze7/DT2vd+5y3BQAAABAWzapd4XPTm1lU7WYUpRSxGqgs+qG3vTf+2c+/t3e//v1HvptaBAAA\nAJxJWDSjdmTTb0Mr4dAqpcm7oR2qLcqjPwAAAACmExbNqFtZ1A2LSjiUImK1aiqNDunnSe0Kom5l\nEQAAAMB5hEUz6gy4HplZtFqlWK9SbM7ZDa19rjOzSFwEAAAAnEdYNKN2ZdETvZlFdWXRbmbRWBva\no01TctSfRTQ6s0hWBAAAAJxJWDSjdmhzs1dZtP1Msa0sGqsG+vinbwfv1//dPiUrAgAAAM4lLJpR\nO7TpzyxqBlxHrAd2Qys+/ulHg/fbe1bOg98BAAAATiEsmlE7tFn32tBKOJRSREopNiMDrruVRb02\ntM6zhr8DAAAAnEJYNKP2GKKx3dBWKcV6FVGNzCz6WLuyaOKA6/5sIwAAAICphEUzaoc2/ZlF7YHW\nh3ZD+0S7smhvwHW79SwGvwMAAACcQlg0o+6A634b2vZzlVKsUhqtLDo04HrsWcIiAAAA4FzCohnl\nSW1o+5VF7YqhX/3Ax+pWtJE8aXtN6/vYsGwAAACAY4RFM2q3ja17YVGuB1ynWKfUaUtrf//+n/2t\n+C9/8B2da5p77N9v+1wAAACA8wiLZtSuBHpiZGbRKkWsVqkT/Nz2Soh+9fc/FhGHQ6CxndEAAAAA\nTiEsmlG72me96v6nrtvOUopV6lYTPdpUnbX//pd9we6Gvfu3D+TuGQAAAIBzCItm1I5s+jOLql0e\nNDSz6HbTDXte8uTN7n7jIVD73KHZRgAAAACHCItmdGjAdRlCnWJ/N7RHuyTpP3vmSztr+yHQ2A5o\n2tAAAACAcwmLZtIfRn3Tn1mUx3dDK5VFX/Hql8erPv8ldfhzKATqzCzShgYAAACcSVg0k36wc9Ob\nWVTVA663lUVDM4tuVqtYpaayqB8CjQ21VlkEAAAAnEtYNJOqX1m0Gt4NLXaVRZ02tF1l0c26GyT1\nQ6B29VJ3ZpG0CAAAADiPsGgm/bhmPTKzaJXSfhvabmbRE+tVrFap1YZ2YMC1fAgAAAC4AGHRTPYq\ni9a9NrSmsChS6g6vLjOLblap14bWtalyfOIzt3vnBEcAAADAuYRFM9mfWTTchpZSxLq/G9qmVVl0\noA3ttz/0yfhT3/kTew804BoAAAA4l7DoMdnbDW0XAK1X+21oZWZRCYuqKW1ore9/90f/Tfzsbz53\nmRcHAAAAXlCERTPZH3Dd/U/9fGfHs+1cohIG3ZZz6xSrVXO8OlAw1H5clSO+8R+9bfK7fviPn4/n\nb6vJ6wEAAICHS1g0k34RUG9kUauyqBl+XY49qkplUdpVFg3PLOo+7/zWs6/4hz8Zf+dHfuHs6wEA\nAICHQ1g0k35l0Spth1UXpXpovVo1YVG/smi1ipRSbCa0ofWrjlIaXrd33e7Ct7zz96ddAAAAADxo\nwqKZ9GOd9WpbJVSUuUTrVdTHq6p77madYp2mVQ3tPW9iWnR7qLcNAAAAeMERFs2kn+9sK4uaAOe2\naiqLSsVRqUYq556sB1wP74bWPCvvBUrr1bSwaCMsAgAAAFqERTPphzcpdVvD6uqh3W5oEU0b2qN6\nwPU2LCqBTr+1rXnW/rGbiWHRo10wNbVtDQAAAHjYhEUzOVZZVAKg9vEyP6gdJK1WzTyisRqgKuf9\n502tLNo07wEAAAAgLJpJP9hZpdRpDauHWK/T3m5ot5uyG9q2sigfa0OLiNx74qmVRVNnHAEAAAAP\nm7BoJnu7oa26rWiPqjLgOtVVQJvezKKbddrNLNpe0w+Eipz3g6RTZxbJigAAAIAIYdFsxtrQSrtX\nqSxap1RX9fR3Q3titYqUmkBnvLJoP0aaGhbdbprQCgAAAEBYNJP+gOttUNS0ez1qhTTr3Z9Cf8D1\nEzfbFrWmDW16ZdHNatof7W1lZhEAAADQEBbNZH9m0TaQKZlMu9VsvQt2SrVRPc9oteq2oY1VFuX9\nFrXplUVV/X4AAAAAwqKZ9IOdlLazifrDrNcpxRd89pMREfHcJz4TEa02tPW2GqluQxt7VuzvhjY5\nLCqVRdIiAAAAIIRFs+kPuF6vxtvQ/sTnvjgiIn7vI5+OiG3V0XqVtgFTSvW9DlUW9Z064NpuaAAA\nAEBExM19v8BDNdaGVip46gHXqxRPveyzIiLiAx/91O5cjpvdulVKdRjUD6Daz+rPM5oa/pT5SElY\nBAAAAIRY+aAhAAAgAElEQVTKotkMD7hu2tAeVU1l0ee86In47M+6qSuLHm1yPLmber1aNSHRWBta\nlc9vQ6sri/yfAAAAAISwaDb7M4u2f5cMpz3EOiLiFZ/7orqy6NGmipt12l2X6l3SxvrQtgOuu6aG\nRaUdzm5oAAAAQISwaDZ7lT67qqISymzqwdLb8694+YvjAx9tZhbd7Ep91q02tLHKosgDzzuxskhY\nBAAAAEQIi2bTny+014a2q+gplUV/4nNfVIdFjzY5nqhnFjX3Gp9ZtP2rbXJlUbWtcFr5PwEAAAAI\nYdFs+rFO04ZWwqJmwHVExCs+98XxwY9/Jp6/reJ201QWrVKqq38O7YZ2dmVR2ZVNZREAAAAQdkOb\nTXvA9TYoSvGyFz0RT643ERFx2xpwHRHx0s9aR0TEp2838ajK9cyi1ep4G9p2wPV5u6HdlsoiYREA\nAAAQKotmU7WymxLEfPff+DPxHV//70REe8B16qypqhy3myqeWJXKotZuaGOVRbEfJJWw6ZgSWsmK\nAAAAgAiVRTNq4ptS5fPKz3tJfPRTjyKiCWlKSFQqjKq8/XvVCpHqsGiktugubWi3dkMDAAAAWlQW\nzaRdWdTOYVL0B1w3g6wjtruT5Zzr3yml2BUhHags2h9wfTM1LOq1wwEAAAAvbMKimZRgZ71Knaqd\n8vV2U20HXq+a2UTb63JsqtyqOGrmH/XnErWflXM3lJpaKVTa4ZLKIgAAACCERbMplT7rlKJdtJNa\nFUTtIdQl3NnkPN6Gdmg3tOgGRJPb0OrKoknLAQAAgAdORDCT3SZjsVp1Q5y6Da2qOoFO+bqdWdS0\noa1Sik1VZhY12oVAOXLkHIOh1DGlsmhKJdLf//F3xvf9zLun3RgAAABYJAOuZ9KpLBoIhW43uTNX\nqL0b2jb42f5OqakoqlqlRSma8GhbWZR3rWR5d59p79kftH3IW9/z4Xju489PuzEAAACwSCqLZlJy\nndVquA3t0Sb3QqSyG1qZWbQ9vh5pQ2vPGMq7f7TjnrGd0/qasOj42rGZSQAAAMDDISyaSclVbnoD\nrkukc1tVncqi0pLWtKE1g6+rgYymfceq2kZD7ccMXTNkc8JuaDmmh1AAAADAMgmLZlK3oa1Spwoo\ntdrQ1qvV3vHNQBvaZmA3tH7XWM65noe0/T3tPR+dshtann5fAAAAYJnMLJpJqez5wpe9qHO8hEC3\nVRXr1bo+Xip7cs6xyTme2P1ep1SHRJ0B162pRXkX4nSGXk9MdTZTS5CiVBYBAAAAD5mwaCYlrPnb\nf/V18dVf/lR9vOQ52wHXTWVRCZE2OXfb0FLThlZ1hha1nrWrY+rOLJrm0Wa/amlMzlllEQAAADxw\n2tBmUjKVJ29W8dmf1WRydRtalaOVFbV2Q9tWJTVhUVP90w5qVr35RNvKotQ6NrWyqKrvcUxVJmkD\nAAAAD5awaCalUqe/JX17rlC3smj7WeUcOTe7oZUAKOc80IYWrXO5W1k0eWZRrp97TA6VRQAAAPDQ\nCYtmUkKV/tjodnbU3oGsrizKOTZV04bW3iWt04XWaUPbnesdm6JULU2pLMpZXREAAAA8dMKimZRQ\nZa+yqB0WtX60Q6EqR6xWTRva9nju7obWftZAMDV1wPXtrg1t2syi6fcFAAAAlklYNJNqV6rT35E+\nDQRE7XWbargNbXt8+D4R22vax6ZmOrcntKFtnwQAAAA8ZMKimZRQZa8NrfX9Zr0fHOXebmjN8Yj2\n1KL2fapde1g7P5oa/tzuQq1NdXytqiIAAAB4+IRFMylhTTrQhtZuUVu1KojaM4u6bWjtGzVfc96e\nP2fA9W2909qUAdfT7wsAAAAsk7BoLmWOUL8NrbMb2tCA620g08wsagZft4dQ95rQtte0Hja5smhX\nUjRlfdXbkQ0AAAB4eIRFMxlrQ2vlQ73d0LafVd2Gtru+hEVVtw1tterOJ+q3oU0NdW5P3Q1NaREA\nAAA8aMKimZRKnXaoExGd9KgdFjW7oW0riOqZRa0QKUYqi5oWtXaAdPnKIjERAAAAPHzCopkMbWe/\n/T22G1p3ZlGpElq1QqTOyKK9nc9yt7Lo5JlFx9fmbGYRAAAAPHTCoplMGXA91IZWWr3Wu4V1iJRz\np1qoH0LlvF9tNMXtprShTVmfw9QiAAAAeNiERTOpZxaNd6F1BlyPt6FtP7c7nrXu06siyvm8mUWb\nanpYpLIIAAAAHj5h0VxG2tDaO5atB3ZD21S7Adercnz7eWgnsrz7q93iNmVgdUTEbbWbWVQdX5tD\nWAQAAAAPnbBoJvWA68ltaKWyaHttaT9rHx8bWl21Kot+7R++If7i656anOo0M4uOr98GVtIiAAAA\neMiERTOpB1zvtaG1K4ua//zla2lDa2YW7Y5X3Zimne3kXdVRiogXPbGOJ9ar6ZVF9cyi42u1oQEA\nAMDDJyyaSclU+pVF7b60zsyi1J5ZlOv2s/Yso3b1Tyc4ilJZlOpHTK0AqtvQJs0skhQBAADAQycs\nmslY+NLOjtpBUmrPLKrG2tCG759zNxxKKU2aQRTRtKFNqiyK6YOzAQAAgGUSFs1krA2tHRAN7YZW\ndj1b9drQNlXutZ61v+eI1m5oKU0PdUob2qSqIWkRAAAAPHjCopnksQHXre/rdXvA9faz7Ia23v3J\nNCFSd7h01WtJy9EKi2J6y9imriya0IYW09vbAAAAgGUSFs2kRCp7I4vau6GldljUn1l0uA0telVG\nOed6ePYqpcmDqB9tysyi42tzzgZcAwAAwAM3KSxKKb0hpfTrKaV3pZS+feB8Sil91+78L6WUvmJ3\n/EUppZ9PKf2blNKvpJT++0v/C1yrEqrsVxbtt55FRKzabWhVtGYWbc+XXdKK7syi3K0sStMqhdr3\nmbK+yrrQAAAA4KE7GhallNYR8d0R8XUR8fqI+Osppdf3ln1dRLxu9/ebIuJ7dsc/ExF/Oef870XE\nn46IN6SUvupC737VSvjSKyzqVhatBtrQcrcNrT34uh3VDO6GVt8rTQ51SgA1bWRRtiMaAAAAPHBT\nKou+MiLelXN+T875+Yj44Yh4Y2/NGyPiB/PWWyPi5SmlV+x+f2K35ond3y+ItGFKG1pnwPVIG1o5\nnnttaP2d0baVRc3QoqmVRSX82UzoQ8sqiwAAAODBmxIWfUlEvK/1+3d3xyatSSmtU0q/GBF/GBE/\nmXN+2/mvuxwlhEkT29DKuqratpvVbWi7P6ESCBWdMKieWbS1OmE7tJIRTR5wLS0CAACAB232Adc5\n503O+U9HxCsj4itTSn9qaF1K6U0ppWdTSs9+8IMfnPu1ZldClaltaOX7bVV2USvrd21ou4qj+v7t\nZ+2e194N7dTKoknLVRYBAADAgzclLHp/RHxp6/crd8dOWpNz/khE/KuIeMPQQ3LO35dzfibn/MzT\nTz894bWuW6kD2q8sagzNLLrdbK9b77Wh5V4bWnvA9fZ57aHYU0OdfFJlkagIAAAAHropYdHbI+J1\nKaXXppSejIhviIg399a8OSK+abcr2ldFxEdzzh9IKT2dUnp5RERK6cUR8bUR8WsXfP+rVW13pI9V\nr7SovTvazUAbWl1ZtEqd9f2dyPZmFrUGXKeUZtkNLetDAwAAgAfv5tiCnPNtSunbIuInImIdET+Q\nc/6VlNK37M5/b0S8JSK+PiLeFRGfjIhv3l3+ioj4x7sd1VYR8aM5539x+X+N61MPuO41orULjVZD\nbWibqrOuLKmq7k5kB9vQ0vRMpyybMN96b25SRMRvPffH8ZoveMleBRUAAACwTEfDooiInPNbYhsI\ntY99b+t7joi/NXDdL0XEn7njOy5SM+C6ezyNVBaVr4/qmUWps37TS3+6bWh524a2C6ZSpMlhUdW7\nz6HQp19Y9O4PfiL+yv/4/8T/8a1/Pv7sqz9/2gMBAACAqzb7gOsXqnrA9YGCmyfWzX/+Eg5tdv1r\n9cyiVZlZ1A122pVA/cqiVeqGSVPes3/PsbXt2qKPfupR5xMAAABYPmHRTMYGXLd97eu/qP5ewqIy\n4HqvDa034Lr3sE57WDpjwHV5xinry3djjAAAAODhmNSGxulKlU5/wHVExNf/u18cf+VPflG88vNe\nUh+rZxaNtaFV42FRPeC63g1t+oDrdqXQoWtKpdLQjmzCIgAAAHg4hEUzqdvQYj8t+l/+8z+7d6yE\nSmXAdfndbkMb27p++6zc2g1teoBT5e0zDoVRzTP2B2v3jwEAAADLpg1tJiXYGaosGpJSipSaAdcl\nJGq3oY3NFNrfDS1N2t0sYlsdVJ51sLKotb65dv8YAAAAsGzCopnUYc0JO8qvUqori9otZfX9xsKi\n3Zb2dVi0PTr5PdftZ4yu2z9Zt6FNehIAAACwBMKiueyClKE2tDGrNDSzaHtuU+XxNrTYbXsf7ZlF\nU15xu+hmSmXRwKkqj58DAAAAlklYNJOSn0xtQ9uuTfVuaPszi8ZnCu1VFqVprWFlyXq9e0Z1YG0M\nDLg2tQgAAAAeHGHRTKpd2U1pJ5tilVLcVrsB16v9NrSxyp+cdzOLWveZUllU7te0oR2vLOpUN6ks\nAgAAgAdHWDSTcyqL1qt2ZVF3wPUmjzWh7drQIprSophYWdR6bsThsKi57/71siIAAAB4OIRFMymV\nPafMLEqdmUWx+5zShlZmFjXXTKn2qSuLVscHXDeVRfvXqywCAACAh0NYNJO6sufEyqJHu93QVnu7\noY1XFpXQpjOzaHfufR/+5IF3bJ7bvs/g2npmUbNmsDUNAAAAWDRh0czOHnDdn1lUxWgJT47+zKJt\n8PPuD34i/uL/8K/iF977R8PX7W43ZTe0aqCySEQEAAAAD4+waCZNtc9pA643vTa01JpZNNYmlnOO\nKuc6WEq7NrSPfPJRRDSfe9fFKW1o+2lR1oYGAAAAD87Nfb/AQ/W1r//ieNXnvzRedDM9j1uliEdV\ntw2tBDk554PtXjl329CqnOswZ6xiqOq3oR1Ii4aGWQ/NMQIAAACWTVg0k9c+9dJ47VMvPemaThva\n3syi8QqenLdVQmWYdooUOVqtYwcqkiIi1qvVwXXtc52ZRQNzjAAAAIBl04Z2RboDrqPzuanGd0Or\nyk5prWtKa1o5P3xdeW4cXBcRg+VDMiIAAAB4eIRFVySlaM0sauYPRXTDn75tZVEz4Dql7bF6a/ux\nB9Zh0fZ/g0m7ofWe2/485J+89Xfi9z/66eMLAQAAgHslLLoi61WK2xIWrZpjEUeGT+/+kerKotRU\nG8V4m1gJh24mDbjufravPzRLKSLiY59+FP/gx385/q93fuDgOgAAAOD+CYuuyCq129DKzKLtuXb4\n01eGX9fVSBG7mUWHdysr59et6qUxQ8FQPfT6SGXRZjeH6dAAbQAAAOA6CIuuyOpAG9qmGt8Nbdty\n1t4NLW1b03bLxzKacnhy9VJ0g6GpbWjHZicBAAAA10NYdEW2lUXdsKgEOe3wpy9HjpxblUVlKPaR\nNrG6sqgOiw7MLBoMho7MRKqf0/0EAAAArpew6IpsZxYN74ZWHRlwva0sKq1ru2qk0v41FtLUA64n\nhEUDkVBVB0iHU6CssggAAAAWQ1h0RVJKcVsqi1a94CePj5HOEbvKot19dsfryqLRAdfbz3b10qiB\nYKiuNjpwWfs5x0IlAAAA4P4Ji67IKkWrsqjbUpZzjKYydWVRuc+qmXNUXzt0XZzQhtb7bF9/LC1q\nZhYdXgcAAADcP2HRFVmvWpVFu+Sn7FRWVeOVRVVvN7SiDotGZxb1nnFowPXAzKK6YuhIWlTeQxsa\nAAAAXD9h0RVJKcXtLljpzx+q8njYkiOiqoauKVvWDz+vtIWt18cri4bO5Xy4cqlZV+5xeB0AAABw\n/27u+wVorFuFQaU1rBQL/U8/9RvjF+6GX5e19W5odWXR6GW755aZRVPa0AZCo/E3i4gmaDKzCAAA\nAK6fyqIr0m4jq4dV91rLhpQIpr+D2u2R9q9y+GY1pQ1tv4poqDVtSDOzSFgEAAAA105YdEXKYOqI\nbnD0nf/J6/fW/rVnXhmf95InImI7z6jKzcyiFM2co4gYLf0p4c26NxB7yNDOZ3XF0JHaokobGgAA\nACyGsOiKtLKiaBcUfeNXvXpv7V/6t78w/uXf/ZqI2M0syvs7qG2OVPSU4zcTZhYV51QWZZVFAAAA\nsBjCoiuybqVFne8DrWg5mlAol+HXvda1ozOLes86lOU055pFee/IsM1ACxsAAABwnYRFV6Q7s6j1\nfZU6VUcR2+CltJvl3T+aNrStY1vW17uhpeOVRaXVrFtZNK20qOzGVulDAwAAgKsnLLoiaWDAdXGz\n6v5R5ciRdodyLjOLutfWlUUjGU29G9ru3oeynKHxR0NzjIavLaHVkYUAAADAvRMWXZF1KyBa9VrP\n1r30qNV1tmtDa36nXqXQ2Jb1VR0WRWf9kDxwr6Fqo+Frj98fAAAAuA7Coisy1oYW0WxvX2xnFpU2\ntO1f5Zqy9PbozKKyG9r2f4OxUKl9j8HKomNtaEdCKwAAAOB6CIuuyGo1Hhat1/3KotytLKpabWyl\nsqjMLBrp/yqzhOrKomr83YZynqnRz0YbGgAAACyGsOiKtIuH+hug9SuLtuubAdc55/qacyuLDreJ\n7bec1RVDB66KaCqKtKEBAADA9RMWXZH2XKL+jKL+74gmUKpyjio3IVHZJa2uLDo24LqecTT+bkMt\nZxM3Q6vvq7IIAAAArp+w6IqkgzOLeruh5e73oZlFmyOzgsrhm12L28kziwaODamqw+8BAAAAXA9h\n0RVZd8Ki7rmb/syiyJ1WtSo3YVM5vtnNIBrLaEpb2GpCZVHdQjYw4fr4gOvePQAAAICrJSy6It2Z\nRYfb0HJu2s1yzp2ZReXazW5idR6p/SlHyzykQ2HOUFY0ta0sG3ANAAAAiyEsuiLt1rN+ONQfcJ1b\nM4py7v4uK0tl0VhIU8Kh9SlhUWdm0f7Q6yHNbmjSIgAAALh2wqIrslqNt6Gt+zOLoqkgqvI2iGlm\nFvUqi0YHXHfDokNZTqlOGp5ZNK0NTVYEAAAA109YdEUOtaHtVxbluoIox3Y3tFRfu/0sFT3P31bx\n87/14b3n1buhnVRZdPjYkEplEQAAACyGsOiKrA9WFvUHXDeh0LYNLdcBU1NZtA1nfuJXfj/+2v/6\nr+MPPvbpzj2qvbDo+Du2q4hK+HPsMjOLAAAAYDmERVcknTCzKFq7n+UoM4v6u6Ft05lPfOY2IiI+\n9fyme4szZhadei4ioqpnJ0mLAAAA4NoJi67IOrUri47shrar50lpG/psZxbF7lipLIrd53AbWKn0\nqXdDO1D6Uw0Ms252SDs2s6hcKywCAACAaycsuiLdmUXdczfr/d3QIrZzinLeBj/lmrKyPyuonwWV\nkGdKG1rufbavnzyzqDq8DgAAALh/wqIr0t0Nrd+Gtr8bWsS2iijv/urvhna7S3821VDUc+qA67qM\nqDZ1BlFZpw0NAAAArp+w6Iq0A6L1kd3Qim5lUXdmUdULi/Yqi3ptaL/8/o/Go81w+U8TNzU3aXZD\nm9aGZsA1AAAAXD9h0RU51Ia2N7Mol2vSbsB1rq8pS293fV+bka3ry+8SUv3w298XP/L29w2+WxMM\ntY5NbkMr10qLAAAA4NoJi65IaUNLqbszWsTAzKJS4ZO2oc92N7RytjfgejM8M6hEN+17j7eK5c41\nEe0B14flkbAKAAAAuD7CoivyxG4u0VDD2bo/s6g14Dpy7HZDKzOLtudKOHOssqg9D+nFT6wH322o\n5ax8P5YBjbXBAQAAANdHWHRFvuCzn4yI4VClzBUqYc4Xf86LImJbhZSjP7OoVBZ1Zxb1Q50S9nzO\ni5+IN/0H/9b22Mi7VQNVRE1l0bGZReVTWgQAAADXTlh0RZ5+2WeNniszi/6Lv/Da+KG/+efir77+\niyJiO2+oDLIuFUmlsqip6BmuLGrmHkV8059/9e7g8POHqojqoddHZxZNq0ACAAAA7p+w6Ip84cte\nNHqu7I62XqX46i9/qj6eomkzW/V2Qyth0W01HBaVip8Uqb52rEpo6KiZRQAAAPDwCIuuyMHKonU3\nCCpSq7KoVBTVbWi9ip5+e1sJcbYDtYfXNGv3j1XNIKPR927fU1gEAAAA109YdEUOhkWlaqg3/jpF\nq0IoNccimsqior91ffu6ct+xPKddcVS3pNXnDmva4I4sBAAAAO6dsOiKvPTJ4Z3IIpqZRf3KokhN\nBVGqd0PrDrgu9rOapn2t3Hd0WHV7VlFvWNHRmUX1gG1pEQAAAFw7YdEVSXtJUKOeRzRwvGlD6wZK\nezOKqgOVRSUsOp4VTa4o6j9HZREAAABcP2HRQqx3f1KrVa8NLTUVRCXwGass2p9Z1Kxv2tCGE512\n8NQfWD1ajdS71swiAAAAuH7CooVYjVQddXdDa45FTJlZlOv1TRvasPalvS60421oKosAAABgMW7u\n+wXo+ntv+JPx1vd8aO94v6KoSINtaBMri1r3KNdOakPL3WPHMqB6ILbKIgAAALh6wqIr861f82Xx\nrV/zZXvH1yMB0CpFbOrZQ92ZRfth0XCl0So11UhjrWLtoKe0nU2vLNKGBgAAAEuhDW0hSmXRfuDS\nVBaVwKeeWTTSdtb/ndq7oZ1SWTRxZtGm2j2vOrgMAAAAuALCooUoXWj9Hc3aA67rmUW7z9tNv5Io\nBn9vK4t2bWhjLzBwIh8416ayCAAAAJZDWLQQN7sk6LYfFkVrwPVuTR0sHa0sKvdIkXb/J4zNFRqq\nHmoqiw5rZhYdWQgAAADcO2HRQpQgqN9allITxjQjsCcOuK7b0JprxwKddgtZf1bRscHV5bnH2tUA\nAACA+ycsWogy4LrfhrZKqQ6FyoDrqZVF5WdKzbVjgU5nZlGUtrLufcY0bWiH1wEAAAD3T1i0EOt6\nwHX3eIqmNW1V74Y23LK2N7MomutWxwZct3dD61UKHcuASsBlZhEAAABcP2HRQpQAqN9allKqQ5gS\n+JTP/tp+u1jVriyK4TCqvnbge78dbczUCiQAAADg/gmLFmI90loW0cwTKrugpckzi7afq5Tqa0fb\n0HL7ey+EOlJbZDc0AAAAWA5h0UKUNrT9yqJm6HWq29BicO3YDKPUOjae5+S9b+X6qZVFwiIAAAC4\nfsKihViNzCxqD7he9cKiowOud58ppfraMd3Kov1jh6/dVRZVRxYCAAAA905YtBCrkd3QUtqvEFqN\nzDfaG3DdmnVUB0wjQ4s6h/sDro+kRk0FksoiAAAAuHbCooVYlwCoF7ikaAKe1e5Ps6ks6t5jr9Ko\natrXStA0FucMzSVqdkU7bFMNvw8AAABwfYRFCzE+syjVAVLdhhbDLWV7A653n6vUXDtW/NNpQ4sy\nsHr/3PBzDbgGAACApRAWLcS6nlk0MOC63g1tu2Y1Mn5of4bR7rpIo3OOik4XWu4ePbYbWj2zSFYE\nAAAAV09YtBBjO5y129BSb23f3pb3ZdbRqgmaRtvQWtfm+lj3c0xTgSQtAgAAgGsnLFqI8cqigTa0\nkbRof8D17h6HFg3epwys3v0+sl4bGgAAACyHsGgh1iM7nHUGXKfm2JD9mUXdkGmVDlUWta8r98t7\n5w49VxsaAAAAXD9h0UKs6gHX3eMpNTuklYKi1Uhl0ejMohIypTRa/dM+vl9RdDgFKmGWyiIAAAC4\nfsKihVjXu5V1A5dVSnW1Uarb0IbvsT+zqLlHxLYi6ZTd0KbPLJpWgQQAAADcP2HRQqx2f1KbgcSl\naUNLnc+9dbn/ez94Gm1DG/hxbBe0/nNVFgEAAMD1ExYtxJd+3ksiIuKZV39e5/i2dWz3/cg9xsKa\nOlxK42vushtaNuAaAAAAFuPmvl+AaV73RS+Ln/5vviZe9fkv6RxP0VQbleqjMt+ob6+yaGgw9lgb\n2tCx0l52bGZRHRYdXAYAAABcAWHRgrzmqZfuHVutmtAntWYPDenPLGoGXDezjkbznPbMot6A62MF\nQ5u6AklaBAAAANdOG9rCpUhxO3lmUW/AdXQri1YpjQY6ubP3WbdS6FgEpLLo8Xjrez4Uf//H33nf\nrwEAAMDCCYsWLrXmDKXWsSH7A67L+qYiaSzQqYYqiybucmZm0ePxs7/5XPzTt733vl8DAACAhRMW\nLVyK/d3QxsOiXliTc2dtSmk0+Gkfz3ufR2YWVc09tKLNJ0/enw4AAADGCYuWLqVmwHU9qHo4Lern\nNFXuzjdKMR78dNrQ9oYWHX7FdkglK5rPNoy777cAAABg6YRFC7dKTeVOpObYkH5VT47cmW+U0njY\nkAfa0Kp6N7TD/n/27jxItvSs8/vznpNZVff27W5J3S211BK0NgKJYZNARhACHOAZsEzIMQwxCJvF\n4zHLQBgmPCbA2BN4CCLEQDgCY8wywNgsM3hYzRiQBgNmE6OttbSEpKGRWupFvd/bffveW5V5zvv6\nj3Pe97zve5Y8J/NkZmXm9xMBmZWVW9WtJiJ/PM/v9VfYWEUDAAAAAOB8IyzacUrEmyyya2htBdf1\nr+traG2TRQ239TzlzA+IKLleH361AAAAAIAxEBbtOKWU5LXT0JrvWzsNzYTBklIdgUPDKpldTet7\nGlrTe8B4+oZ3AAAAAAB0ISzacX4utKizKJ7qMcZEj+8ouA6uh6egLcommk5SAwAAAAAA5xNh0Y6L\nO4dERJKWf9V6Z1H0eGmf/NG6Plmk3YRRN8Nk0UbEIR4AAAAAAMsgLNp1UeeQiMg0bf5njYMarU2w\nsta1htbVZDSss4gkY216hncAAAAAAHQhLNpx8RqZSFdYVP86LMPuWEPzV8mi2xZ2FmnvOkkGAAAA\nAADnGmHRjgtOMysv00RJ04FotYJrMcH9iimjxaeh2Uki0/TNBnlQjk1atC5ViMfvGAAAAACwPMKi\nHeeXWfv9Q03TRXGGYEw4maRUOAUU3tcLfMpL7UKj7nAi7CzqvCtWUAvxAAAAAABYAmHRjvPLrP0p\noQzbq+AAACAASURBVGlSHy2qFVwbI0niF1yrhcFP8bjmyzZ+QERnEQAAAAAA5xth0Y7zJ4uCsGhS\n/6dt7Czyvk5Ue/AT3h5OsCwOiyi43oS+4R0AAAAAAF0Ii3Zc2DlUfTFJmsKiemeR/xilVOuamA56\nh+xlvzU0/zkJMtbHhXcsogEAAAAAVkBYtEfCzqKmNbTw6+I0tOg+fQquo+dbOFmkmSzaJH7FAAAA\nAIBVEBbtOD8g8muKmgqua5NFppgmspSS1nZk0zAdZKJ1tDaaguuNICQCAAAAAIyBsGjH+ZNB/vVJ\nw2RRPSwyUWeRag1+/IkjFxItU3BNWrQ2rJ8BAAAAAMZAWLTj/LDHnxI6apgs+vgT1+S33vug+9oY\niTqL2tfEmm6ubusOKUxD3xHGR8E1AAAAAGAMhEU7TgVraF7BdcNk0V/c96R8769/wH2tjQknk6Rf\n0GDv07d/iNPQAAAAAADYHYRFO061XG86DU1EZJ4btwqmTdx51LGG1nQaWvR1m2ANjbBo7VhHAwAA\nAACsgrBox7VNFjWtoVlzrUWkCBVUlDbZMOetH3xEXvtDfyCn81xEwsDHhRFRaNQmPA1twZ2xNBvo\nkccBAAAAAFZBWLTjhhRcW/O8ChXiNTSb/Lzl9z8sT16byYOXb7j7WrXT0BakE9oYmZRHtS26LwAA\nAAAA2C7Coh0XnGaWVF9NuyaLsnKyyJio4Fq5AOjmk6mIiDx1bVbct2F+SPedLDIiafnemCxaHxNd\nAgAAAACwDMKiHVebDCpNOyeLirBImyhsUtXU0M0nExER+dTTHZNFPdee/MkiOovWJ/53AQAAAABg\nGYRFOy4uqLbaCq5FRGa57SwKH6NEuTDHhkWPPnPq7mu59TP3dTcTTBYRZAAAAAAAcJ4RFu04f7LI\n20KT6aRjDS23p6GFo0XKmyyyIdKnni7CImk6Da3nJIs2RiblWhxZ0frEIR4AAAAAAMsgLNpxSpr3\n0KZJ+xpaVk4WiZGGzqLC9VlxClrzZFF52TP5ybVhsmgD4hAPAAAAAIBlEBbtumCyqF/B9cx1Fpmg\ns0hJFQBdn2UiIvJIOVnUFPJUoVH3W9SmCq8ouAYAAAAA4HwjLNpxYUG111nUWXBdFVOHk0VV8PPs\nWTFZZMOisOA6LLZuOinNZ4yRNGWyaN1M7QoAAAAAAMMRFu24sOC6ur1rsmjuTxbFnUXldTtZ9Piz\nZyLSsoYmYWjUpjgNzXYWkWSsS9/wDgAAAACALoRFOy4Ie8Q/Da1jsijTcs8nL8t7H7giKjpNzYY5\n18rJonluZJ7raLKouNQ6/LqNDk5DW/QTYVXkcQAAAACAVRAW7bigc8j710w71tBmuZa/+7+/XR6/\nehZMIympwpzrs8wFUafzPJpWCU/dWjTJorVx4ZUmLVojfrcAAAAAgNURFu24eDLI6pwsyqtQQQVp\nU3EamtZGrs9yue2mYxERuTHPgxyiOnVrwBpaymTRulVraAAAAAAALI+waMepaDLISpP2f9qs7CwS\nqXceGWOKcEhEbr90JCIipzPd2FnU9nWsWEOjs2hT+B0DAAAAAFZBWLTj/J4iP/hJVfcaWvV4Ca4b\nI3LtrCi3vq0Mi27M82B9zHUW9RxlKQqumSxaNzIiAAAAAMAYCIt2XHyamTXp6CwK19BUcN2IkWuz\nYrLIX0MLJoui9bNFnUUmKLgm0VgXE3VJAQAAAACwDMKiHRdVDjlJx2TR3J8sitbY/Mmi591UThbN\n8vA0tPiyx2SRnXQiLFo/fsUAAAAAgFUQFu24toCou+BaN96eKCXGiFyfRZ1FtdPQCm7CaMF79Auu\nCTLWh98tAAAAAGAMhEU7Lmk5DS3pCItmmW68LqoIdq7Nismi2y8Va2in82iyyMSX3SmFZg1tI6qJ\nL37HAAAAAIDlERbtuHCyqLrePVlUhQmn5clnIuUamohcPys7iy5VnUW+uBunK5qwQRIF1+tn+vyD\nAAAAAACwAGHRjjtKq39Cv6w67QiLMm8N7XQe9ReZKhx67sWpiJQF1w2lRXHRdRP7vYTOIgAAAAAA\ndgJh0Y47maYiEk4YiXSHRX5n0VlWTQ0lSok2RnQ5/nPT8UREioJrXc+K+k0WRe9n0coalsdpaAAA\nAACAMRAW7bjjSfFPGEdDXWHRLFhDCyeLjIjkZaBzqQyL4oJrm/f0mRKy90miNbSnr8/ljz7y6MLH\nY4CoSwoAAAAAgGUQFu2443KyKO4CSuNRI888WEPzO4uUGGNcwHM0SSRNVLmGVj3eTbC40aL2dMJ+\nK43W0H77fQ/Jf/1/vluunWXtPxwAAAAAANg4wqIdZ9fQYvao+iZ+WJR5KZOdLLJraIlScmGayo2Z\nDlabaqehdbw/GyzFBdezTIsx4etjNZyGBgAAAAAYA2HRjrNraLG+nUU+pZRoI5KXAU6aKDmZpnKa\nxZNFoV4F11Fnke6TNGGQPoXjAAAAAAAsQli049omi7rW0G7M8sbblYiIMW76J1EiF44SOZ3lIkFn\nURj4dE2y2OCimiwKS5iZghkfv1EAAAAAwCoIi3bcyXT4ZNGNeUtYZNfQvFLqC9O01llkxetoTexz\n2fdjh5r6PBbD8KsEAAAAAIyBsGjHHU9aJos6w6LmNbREKTHGC3hUsYZ2Y54HJ5/FU0Gda2jl5SRa\nQ7OP7XOiGvqpAjh+pwAAAACA5REW7bi2yaKbT6atj7kxaz6BTEkR3tjpn8SGRbNosmhAwbU/pRQ8\nhsqitSErAgAAAACsgrBox7V1Fn3h3c+VH/naz5Z/9OUvr32vcw3N+AGPyIVpKqfzPDwNzU0FlV93\npBNxZ1HuSpgpYx4bv0oAAAAAwBgIi3bcScsamlJK/v4XfppcOpnUvne9reBaqaKzSFdraE2dRdX1\nxfGEcZ1FxZ+ajkIiCq7Hw/oZAAAAAGAMhEU77rhlDc1KGk5FO+04Dc0Y46Z/EqXkwlEqp3MdhDq1\nVbKuzqLaaWjl7e4OnW8fSyAzAgAAAACsgrBox7VNFllNNdenWXPBtVtD01XP0Mk0KdbW/Mmi2mV7\nOhGfhmafm86i8fG7BAAAAACMob6jhJ3SVnBtNU0WXS8Lrr/oZc+T/+YNL3O3K1FixIg2IvYwtUQp\n0TqMg+y6U7xS1iQ+DU0PeCwGYrUPAAAAADACJot23PGiyaKG0aLTeTFZ9E2vv1u+4lUvcLcnSRHe\n5Ma4SaA0UaKNCY64dxNFS5yGFq+hEWyMjwAOAAAAALAKwqIdt6izSDWlRSUbCLn7ShUM2YmkRCnJ\ntWksuK5ONFs8WjSJ1tCEyaLREbwBAAAAAMZAWLTjjicLwqKO702isEiUuNPQ/LBIm+bpobi7qInN\nhtJoDa3PYzEMPVAAAAAAgDEQFu24rsmh4vvh10dp9U8+ScN//kQVaVGuxVtDKwKecHoomgrqHCwq\nvhmfhqb7TCVhKfxOAQAAAACrICzac3HB9cXjquMonixSIt4aWvX4vFZwbS/DKaEmbrKoDKbiYmty\njfHwuwQAAAAAjIGwaM/Fk0U3HVUH4NU6i+wamjGukDopC679RCgeKOqaZLHfizuLyDXGZyM9frcA\nAAAAgFUQFu25eE3t0nEVFk3T+mSRMSK5NpKWj0tdZ5F3Glq8Stbx+va+Nph69iyTH33bR2Se6eA5\nsDqmtQAAAAAAY5gsvgt2WdxodJO3hpYm9c4iI0a0qUKmRBXhkdbl5JEXHPUJJ1xYVD7fz/zpx0RE\n5NYL04WPxbL4pQIAAAAAlkdYtOfizqKbvMmiptPQtC5WxWz3deKdYpYoJbkx8l3/6r2iRHnraO3h\nhJ0cUqoInmyH0TzX5WMxFn6XAAAAAIAxsIa25+LOIn8NbVJbQ6uCIX8NTaSYLvKzpQ8+/LRLJzon\ni8rLRKlacFU8lohjLKyhAQAAAADGQFi05+LhoYtH7ZNFiSrCm9yYag2tvI9/m0gxfRSfbNYkmCyK\n34wwDbMO/E4BAAAAAKsgLNpzSuKC66qzaBJ1FqlyTaxYQ7OdRc2TRdp0LZ9VbJCklAoer6LvYwz8\nMgEAAAAAq6OzaA/8m297vVy+Pmv8Xrz55XcWpUl9Dc0WXNvv2e6iLDfBGlmu+62Q2fsoqfcnlfdY\n+BzohzU0AAAAAMAYCIv2wOte+rzW76mOgutpWp8sMsaunBW3hZNF3hqaN1nUFRr5nUVpY2dR60Ox\npH4zXwAAAAAANGMNbc/FNUGXuiaLVHHCmdZVwbUNiDKtgymlXJtqkqXj9f3OoqbBImKN8fC7BAAA\nAACMgbBoz8UBzcUjv7MoDouKKSFtqikiGyjFk0W5NxLUeRqa7SySsODaTjwxWTQe06NwHAAAAACA\nRQiL9lzcE+RPFk3SuLOoXEPTVbBj850sLrjWXljUMdPiF1w3rqExDzM6wiIAAAAAwCoIiw7MhaP2\n09CScg3NGOOKrZOWyaJ53m+yKFxDqx7PFMz4+FUCAAAAAMZAWLTn4smiztPQVBHu5P4amldwrYLT\n0LS73iekSJSq9SeJEBaNqeqQ4pcKAAAAAFgeYdGeize/Lkw7OovErqFVYVF4Glp1X2+wqN9kkYTh\nlA2eNGnR6PiVAgAAAABWQVi05+LJIr/gOmk6Dc0Up5zZYMfeJ9MmCHv8yaKu2SIbXCRJ/b1gXGRE\nAAAAAIAxEBbtuTiemabt/+RKFYGDP0Vk775yZ5Go2pTToscu4/0PXHF9SIfmUH9uAAAAAMC4CIv2\nXBzQxNNEwX1FFWtopr6GlgWTREV4ZHVFFPZ7StU7korvjxdw/IdHr8qbfvIv5J0ff2q05xzLu+5/\nSr7x598hWa4X33lFZEYAAAAAgFUQFu05peq9RO33lXINramzqFgls4KwqCOdMO40NNW4hjZmsHH1\ndC4iIs+eZeM96Uje/8AV+bO/fkKuneVrfy0KrgEAAAAAqyAs2nM2nvna17xYRESed9NR533tGpqd\nArKXudZB2NN7ssh2FikJCrLt1TFjDfuWzuNkzSZOKjuPPzcAAAAAYPcQFu05G/B84+s/Xe5/yxvl\nxDsNrXbfpFhD06ZaV7MBT1brLKrWqbo7i4pLJeFkkX3ImD07NsA6jyes2ZBonW9tE68BAAAAANh/\nhEV77s5bT2SSKLn9UvtEkaWkCFq0qQqubcAzy7RMkpbJoh5raMVkUVNn0XhsSKTPYVhSTRZt4LU2\n8BoAAAAAgP012fYbwHr9rbtulXt/8O/IhaP2iSLHOw0tVeEa2izXMvFOUstNvzU0F9yosFzbhkhj\nTsHYDu7zeCrYOiapaq9x/n5sAAAAAMAOYrLoAPQKiqSc/KmtoRWXxohM0+bJoq60yK5GJUoFnUVV\n2DRewrELk0WbeI3zGJYBAAAAAHYHYREct4amvTU0L+FJE7+zyJ5y1q/gWkm4hlZNAY3wxks2gDqP\np4G5PqGNvBYAAAAAAMtjDe0Aff9Xf6Y8fOVG7XYb/OTGOw3NC3imibeGVqY9qVILOouKyyRRQfBU\nBTvjMTswWbSJgmsAAAAAAFZBWHSAvu3LXt54u5Ii+CkKrsPT0EREJg1raIlSCzqLygmk6Ln0GjqL\n8nPcWWStM9DZRCAFAAAAANh/rKHBScrJomINrQyLvIQnKLjW3hpaZ2eRlPdTwRqafcyYx9xXnUXn\nLy1xAdZG3tr5+/kBAAAAALuDsAgVpcSYaA3ND4saOosSpeTGPJf/4y8+3jjR4yaLVLjSZo17Glr/\naaV3fOxJefYsG+/FF9hEVkREBAAAAAAYA2ERHBvlaF2EOyLRGlpSX0OzYdIP/tu/kvd84nL9SW1n\nkVLSkBWNupalTXjZ5tpZJt/wc++Q37rnwdFeexF39tsG0qJzOFgFAAAAANghhEVw7JpYprWbAvJX\nx6b+Gpo3MWTNMl17zrCzqDEtGk3ecw3tLNOSayOn8/r7XZdqsmj9SQ5ZEQAAAABgFYRFcGyWk+vm\nNbS0YbIoCICasiBvssh/vPv+iu85fC0TXLbJypPcNnl6mH0tTkMDAAAAAJx3hEVwbJSTayOqYbLI\nPw0tK48e8/Ofpskhv7OocbBo1NPQ7GTROPcb00Y6i1hDAwAAAACMgLAIjg1zMm3EbpwFa2hJ/TQ0\nf1qoKSyqTkNr+/74nUWLwpIsX/+UT6zqLNrAGhppEQAAAABgBYRFcOw0Ua6N6ywKTkPzJ4u0CR5T\nXK8/p3GdRS1raGs4DW1RZ5ENuja6tmU2sYYWXgIAAAAAsAzCIjj+ZFG1hlZ9Pyi4dp1F3uMbntN1\nFiXhfd33V3nDkXxoZ9EWJovW+hpMFAEAAAAARkBYBEeJN1lUJjuJP1mU1CeLkgWTRXY1TIkKppCs\nMQMO7U5D675ftsmyotIm+4TIjAAAAAAAqyAsgmOzoFwbdz31Ap40rYc9YVjU3kmkVPhc1ffH03cN\nzXYW6Q2GRu40tDXOGFVraKRFAAAAAIDlERbB8bMcO1EUnIbWsEfmdV43rqHZPCZR4X2dMTuLek7v\nVJ1Fm7OJySImigAAAAAAYyAsgqO8uMdOAfkBz6Qh7fFPSGsa1KnWzNTaT0PL+04WbbGzaCMvSWgE\nAAAAAFgBYRGcYLKo4TS0acMaml963dU/lChpDotGnSzqd+KYXUPb5LpWNVm0iTU0AAAAAACWR1gE\nx+8calxDSxsmiybV95smi2yAo5RqPA1tzNqgquC6+0ndGtpGJ4s2sPrGHhoAAAAAYASERXD8LMet\noS3oLJoEa2j1sMLeVHQWrfs0tPCyTebCos3voa21s8hekhkBAAAAAFZAWAQnXEMrLsM1tPqfy1Ha\nHRbZ4Ea1dhaNpyqu7jlZNOJrL2Iarq3vtUiLAAAAAADLIyyCkzSuoVXfT5smi7weo7I3OmDcGpo0\nrqGNOQVjenYWzfMtFFz3fG+rvcb6nhsAAAAAcDgIi+A0FVwnCwquJwsmi+xNSjWHTWNO2pQZkOgF\ne2h9J5DG5Aqu1/kasv5ACgAAAACw/wiL4ASdReVfRhp0FjUUXCd+wXVDWFQGGIlSQYG2+/5aCq67\n75dtoeDavqdNvCZZEQAAAABgFb3CIqXUVymlPqqUuk8p9X0N31dKqf+1/P4HlFKvKW9/iVLqj5VS\nf6WU+pBS6rvH/gEwIn8NrangumGyyO8xagpCtDdZ1LiGtuRbbTL4NLQRX3uR6jS09b0qE0UAAAAA\ngDEsDIuUUqmI/KSIfLWIvFpE3qyUenV0t68WkVeW//OtIvJT5e2ZiPx3xphXi8gXich3NjwW50TS\nuIZW3dY4WTSpbssbRnqq09BUMKUUf38MNiRa9JS2s2hRqDQms4HJouo1SI0AAAAAAMvrM1n0OhG5\nzxjzMWPMTER+VUTeFN3nTSLyi6bw70XkOUqpFxpjPmWMuUdExBhzVUQ+LCJ3jfj+MSLlLaLZfqF0\n0WTRgjU0e5sSaV5DW0Nn0aKwxIVaW8hUWEMDAAAAAJx3fcKiu0TkAe/rB6Ue+Cy8j1LqbhH5fBF5\nx9A3ic0ICq6ThjW0hj2yaVBwXX9Oe5NSKngu9/01nIa2aGIoW3EN7fGrZ4Mf405DW+caWu0KAAAA\nAADDbaTgWil1SUR+Q0S+xxjzTMt9vlUp9W6l1Lsff/zxTbwtRMI1tPIyqU8b+fxpo6aJHntbcRpa\n/TXHzDXsxNCigmvXWbREUvV7935KvvCH/195x8eeHPQ4+0rrXUMjJQIAAAAArK5PWPSQiLzE+/rF\n5W297qOUmkoRFP2KMeY3217EGPOzxpgvMMZ8wR133NHnvWNkwRqaqodEjZ1FiyaLvM6i5smiEdfQ\nhk4WLfHS777/soiI3PvQ04Met8kcZ53TSwAAAACA/dcnLHqXiLxSKfVSpdSRiHy9iPxOdJ/fEZFv\nKk9F+yIRedoY8ylVlNT8vIh82Bjzv4z6zjG+hoLr4npx2TRZNPUmi/IoEXn4yg158tkz99RNnUVj\nci+/ICvJXMH18NewP2828MHuNLRNdBaRFQEAAAAAVjBZdAdjTKaU+i4ReZuIpCLyC8aYDymlvr38\n/k+LyO+JyH8qIveJyHUR+a/Kh3+JiHyjiNyrlHpfedv/YIz5vXF/DIzBj3L89bMiODLNBdfeZFE8\nJfTFb/mj4Dma1tDGPJGsWkPr21k0/LVtYNZ08lsXd1LZOjuLCIkAAAAAACNYGBaJiJThzu9Ft/20\nd92IyHc2PO7PJcwgcI4lweqZeNdVcOkL19A60golay+41m4Nrft++QpraLbke26PXutpE51F7rUI\njQAAAAAAK9hIwTV2g2pdQyvDooawx19D0x35SbLRsKjfZNEyJmU4luXLTRatk1t1W/9LAQAAAAD2\nGGERnPawqLgcMlkUT96otoLr8vKxq6fy2NXTJd51xYZVi4IZ21m0TLm2/R0MD5zWH+QwUQQAAAAA\nGEOvNTQchuA0tKR+vamzaNISFj17mgX3KyaL6q/5T37t/fJPfu397uv73/LG4W+8ZAu2F4VAbg1t\nideYuM6igWtotrNoA4nOJl4DAAAAALC/mCyCE04W+dfLsKgh7fFv8odtnjmdh88tKijNXoe+nUVZ\nzyLsJjYcmy+5hrbWyaLoEgAAAACAZRAWwVENPUUi1cloaVL/c/HjHz98uRpNFqmWzqIx6Z4h0CoF\n17ajKRs6WSTLv2bv12CiCAAAAAAwAsIiOH6UE5yM1jFZ5AdMnZNFLWtoY7Kvv3iyqOwsWuI1UreG\ntmzB9SbW0Nb+EgAAAACAPUZYBCcIiBJ/yqi8bAyLquvaC1CeuRF3FqnGguwx5abfIpY9yWyZUMUG\nZoNPQ7OX65wsargGAAAAAMBQhEVwgs6ipL6G1jhZ5F0P19DizqJwCmkd7BrWog2x6iSzJTqLylW8\noaehbaKziIwIAAAAADAGwiI44RpadT11nUUNYU/rGlp9smjda2j5wM6igbVDIlKdCDfPz2Fnkb0k\nNAIAAAAArICwCI4/+JM2lF0vmiwyXZNFqiVsGlH/zqIyuFliFMf+iEPX0OxLbaKEmqwIAAAAALAK\nwiI4quEENJFqyqgp7Ak6i7wgJO4sUkqtfQ1Nu1POFnUWlQXXS6QqNmAavIYWXa6D/bmZLAIAAAAA\nrIKwCE7raWius6j+56K8R/mbWf5kkX2q9Z+GZieGulWTRUu8Rvkz5gN32DYR5JARAQAAAADGQFgE\nRwUBUXW7DY6GTBZd9TqL7F3SNU8W5W4NrV9n0XKTRYXlJ4s2sYZGbAQAAAAAWB5hERw/C1INnUWN\nYZF3PegsOqsmi+zjkw2tofXuLFoiLbKPGdpZZDawh+ZOXCMrAgAAAACsgLAIjp/lHHmjRTYkWnAY\nWhDSzDJdu8+asyI3UbR4sqjsLFriNexj8vPYWcREEQAAAABgBIRFcPz+oVsvTN31RBUnoTUVVIed\nRVVY4a9pqY7JpDHlPSeG5vnqk0Xzc9hZ5F5r/S8BAAAAANhjhEWoeFnOzScTdz1JVHvQ493shy9+\ncGTvsu41tL5rWPkKBdf2uQevobnL9UU51c9PXAQAAAAAWB5hERw/zLl0XIVFqVIyaQmL/Fv9zSw/\nTLHPu+41tLznGlq2hYJr6RlkrYKMCAAAAAAwBsIiOH6WM/E6ixLVPFkUhz+6bbKovN+619CqzqLu\n+63UWWTC5+j9OFl+mgkAAAAAgE0iLILTNvmTJM1BT6JUMM0STBZ5YcqmT0NbtIZlp54WTSA1vsaK\np6FtYkWMCSMAAAAAwCoIi+C0hTlpoiRNij+VX/wHr5Mf//rPK+8fBi7h9erxm+ossq+5aLLIrZCt\nsIY2vOB66Zcc8BqkRAAAAACA1REWwWmLchKvs+hLP+MOefkdl8r7K9cTJFJN9oiEk0U2I1rzFlrv\n09Cqgutl0qLiMfnggusNpEXxawEAAAAAsATCIlTKMOfCNA1ujjuLbPijVDjF41/3wxS1qTW0np1F\nNsjaZMF1NVm0xtPQotcCAAAAAGAZhEVwVJkWXTqZBLeniZJJqoKvRYrwx58m8tfQ/DAl2XjB9YLJ\nonz509Dszzs0LHKbb5yGBgAAAAA45wiL4Ngs5+bjSe12P+hJ3aRQe2dReBqaKi9Hf8uBvoHMXC9f\ncO06i/JhnUX2kZsIdAiNAAAAAACrICyCY0OdeLIoUcoFRCIiiTdZlA+YLNrUaWgLJ4tcZ9Fw9qnz\npdfQ1seuuJEVAQAAAABWMVl8FxyKWVZMy1yKJou+7gteIk88e+a+TrxJIT+XCfqLgjCluP/QNbS3\nfegR+bLPuENOog6lNjYkWjRZk+Vb6Cyyl2sc+3GBFKNFAAAAAIAVMFkE59mzuYjUw6L/5NUvkDe/\n7tPc124NLQlPQzMtk0V+IfYiNmR68PJ1+bZfeo+89YOP9H7/ed/OIvfellhDK587G7iGZh+33ski\nAAAAAABWR1gE5+ppJiL1NbRYUv7VKIk6i7z8xF/Tsnfps4Zmn+/aWS4iIs+eZQsfE79+386ipSaL\nyscMHCza6EllhEYAAAAAgFUQFsG56zkXRETkdXc/r/N+baeh5cFkkfYmiUzwuC72Oc6yvLzsP8HT\n+zS0VTqLloxiqre0/jU00iIAAAAAwCroLILzxa+4Xf7gH3+pvOL5lzrvV3UWKfG3sarOICPaiBxN\nEpll2pssWvwe7HSQDYlsaNRH3qPg2hjT637tjw+fS/Us7d7MZBEpEQAAAABgdUwWIfDKF9y8MADx\nwx8ddBYVlzaMOU6LPy97nyFraGdzHVz2YYecuiKTpvW4Ifz1syEl15voLHKvRWgEAAAAAFgBYREG\ns2FEolTYWWTLn8sQ5WiSlPcvfNaLbpXv/I9f7tbdmoyzhtZ+Hz/gWXUNbT6w5FpkvZNF1Wlo63sN\nAAAAAMD+IyzCYLplskhHk0U2LNLe1//93/nM2mlrwXNrGxYVQczpvP8amr8G1yYIi1ZcQ5vnQyaL\nyst1dhat7ZkBAAAAAIeEsAiD3XnLifztV79AfuIbXhN2FunuySKraxvNZjnLTBb16SLKBwQ8XGT/\nJgAAIABJREFUiwyZLNrkahihEQAAAABgFYRFGCxNlPzsN32BvPbTnxtM59iQxk0WlZ1FcXbT1Ylk\nH+s6iwYUXLtj7TsynMz75jIF1/7pb4PCog2siLleJNIiAAAAAMAKCIuwEr8wuuosKkKUqQuLwvSi\nq+bauM4iHVwOeS/rLLj2HzLPlllDWx8yIgAAAADAGAiLsBK/TFpHkz2us6g2WdT+fLWC60GnoS3u\nLJr3CIv+9Ts/KT/6to80fs9/TD4gbbJraMv0JA21r6eh3ZjlG/n9AQAAAMChIyzCSoKCax1OFlVh\nUfgBP1nTGlp1Glq/zqK2UOVPPvq4vO1DjzZ+z3/MkDW2TWQc+3wa2tPX5/L5P/Tv5E//+oltvxUA\nAAAA2HuERVjJHTcfu+txZ9HxEgXXNuhwa2iDJovCyyZ+Z1FbqGLEtE6w+M89ZMrF3nMTnUX76JnT\nuZzOtTz69Om23woAAAAA7L32M8yBHr71S18mL37uBfmFP/+4C1LsaWi2syhOi7o6i9xkkTsNrf9k\nkess6pos6rGGpk1HqON9Y0C/tfsdbGJFbB8jI7PB3x8AAAAAHDomi7CSaZrImz7vLkkS1X4aWvQB\nv/M0tCULrv2AqGvAJvPDopbgwZj2wMW/fdAamuss6v2QwdxT7+GE0SZ+fwAAAACAAmERRpEo5T7I\nZ2Uv0HSJgmt3Gtp8WFjUdCpbkyyvh0pvv+8Jedn3/65cuT5z76HtOfybl+ksWmvYsYET17ZlE6fJ\nAQAAAAAKhEUYRaJEHr96Ju/42JMuRHGTRVFC0r2GVlza9bPTeb81tKZT2ZoEnUXl5U/80X2ijciH\nHn7G3d6+otZvgilmoksMs4nOJwAAAABAgbAIo0iUko8+elW++V++0616HbVMFnWdhqaNkbu/73fl\nt9/3sIj0nywKTmXr3VlUrs2Vl/Z9dU4WtbzmIva11llCvc+Bivv9EbcBAAAAwNoRFmEUNmg5nWvJ\nyvEgexpaLM6KnntxKl/5queLSLgmJiJy1nuyaFhn0SRRLnbQ5W1posrn6jgprecEU+1x0eU6bCKQ\n2pZ9DsIAAAAA4LwhLMIoEu8v6bTsGzpqDYvCtOgrXvUC+fov/DQREbk+y4LvLdNZ1BWWuD6lNHFh\nj50ssmGR6XgOf7IlH5AWmU2kRXuMziIAAAAA2BzCIozCXy2zPUO2sygWL6EpqYKa69EkUaaNm1Tq\n4lUR9eosmqbKJRB5NFlUrKE1P97PkIZM8FRZ0QbW0Nb2Ctu0v1NTAAAAAHDeEBZhFH5YZKeBpm1h\nUZQWJUq5227M6mtn8XTRb733QfnJP74vuG1oZ9E0TVyo4sIi11nUHuqY4HVaX6bpgf7FWmzkxLUt\n2eefDQAAAADOG8IijCLxAiA3WdSyhhYXXCvlTRb1CIt+/95H5DfveTC4Le8Z4rjOolS54MGGRfZt\n6Z6TRYMKrqPLddjn8ueqs2h/f0YAAAAAOC8IizCKYA0t6w6L4skipZSb6rkRdRaJiJxlYYCUayPz\nqAg7DG4WTxZNksSFK3H3kOkquG59zW6bnIzZxziFziIAAAAA2BzCIoxCBZ1FCwquo9aiRFWPb5ws\nmoeTRZk2Mo96jGxn0SRRnZNF9nFHk8Q9xk4lae+ybYIlWHfr170tItXUz1o7i1wgtX+Rivv97d+P\nBgAAAADnDmERRtG4hpbGVdaF+mTRsDW0rsmiNFE9O4uUi220tiFR8bWR9gmWpdfQNjBZtM85CpNF\nAAAAALA5hEUYReqlRWdlWNRecB1PFikXNt2Y18Oi0+i2ea5rk0XVeply4U+TzF9DKxOITIeTRcVp\naItjiaXCot6PgG+fp6YAAAAA4LwhLMIomk5Day+4rj82cZNFTZ1FTZNF4W02Q0gT1Tm9408WWW6y\nSFerTm2Bkx9WDMkt3F03MFq0j3nKPpd3AwAAAMB5Q1iEUajGNbS2zqK6quC6XgQUF1w3dRZl2gZU\naWeskJWPm6ZJdRqa6yqS8rI9mli+4Np2Fq3PPgcqmywIByytjfy7Dz3CRBsAAAAODmERRpEMKbhu\nXEMrw6J5fbJo1tJZ5H+As6tkR2l3Z5FbQ/PuZ3Mn7QU6bU/hP3d8ilqXzZ6Gtr8fbPf5Z8P58+5P\nXJZv/aX3yPsffHrbbwUAAADYKMIijMLvLDotJ4H6r6GJJOVdr50Vj/2az32R/PjXf56ISK3M2gY+\n/u1ZeX06SXoWXCdVwXXtNLRiEujJZ8/kmdN58Piw4Lr1ZWqq07w2cRra2l5ia/b5Z8P5Zacazxq6\n1AAAAIB9RliEUTStoR23hEXxIpp/GpotuP6hN32WvOqFt4hItWJm5eXX/iqavc80TTpDnMwPi9xk\nUXQsuzGijch3/PI98sP/z4eDx/tPPST42UTBtYku94kL27b8PnBYKKYHAADAoZps+w1gPzQVXLef\nhlZ/rFtDm9mgKXUBUrzuZQOfzJ8sagiBmvinprnJovg0NCnCicvXZ/Kc69Pg8ctPFtUfj/6YLMI2\n8N8tAAAADhWTRRhF0lRw3XMNTXlh0bXyNLSjSSLTcjettoZWfj3zJotsCHQ0STo/2M29gmv7STBz\nYZGUl8Vkkb30+UHUuSu4tq+xhx9sq6mpPfzhcG5V/93ydwcAAIDDQliEUTQWXLeehta+hnY6y2Wa\nKkkTJZPyePssrxdci4RraPb6ooLrXJuyI6maLMqjziJTjBaJMfVVs3CyaEBY5B6/xs4id7l/H2z3\nOQjD+WVqVwAAAIDDQFiEUaggLOqeLKqvoVXTRtfnuZxMUhERFxbNa2to9c4iv7h6UWfRJEkkUV6h\ntessqiaMiqkiUwuE/CBmSFi0zIfNsyyXx66eDn/gHtpE2AbU0FkEAACAA0VYhFH4H+JdWNQyWZRE\naZHfWXR9lsvxtHjcpFxD6zNZ5E5DK1+zLVTItZE0KWab7F3cZJGufhYjNjSKf87qetS73WmZ7pPv\n+lfvldf98B/2f4097vXZ558N59c+TukBAAAAfRAWYRR+r9DpXAerZTVxZ5EUa2EiIrNMy3E0WdRW\ncD3L6gXXdppJG5Hrs0zuf+Ja9D61TBIlSinvOHspH1N9rY0RI/XJIv+tLNdZ1P8xf/BXjwaPPWyc\nhobt4T9BAAAAHBrCIowi98ZszrJcJolqDYviySKllKTebXayqK3gOi+/zrQ/WRT2JBlj5Jt/4Z3y\n5T/2/0Xv00iahpNFlg2CjJgiMNL1+xgxbo1umS20ZT50xmHZIWKyCNtgvP+bAAAAABySybbfAPZD\n5gUap3MtaaLctFAsvlUpkcSLLePJongNLWtaQ4smiz7/n/2BXD3LGt/nJElEVEMQ5HUWFZf1ySIx\nIqlSkjV9r0P1oXO43JiF/6H600f7OIm0z+XdOL8IKQEAAHComCzCKPzpl9Msl0mSBNNCvnrBtQqm\njY4ntrOou+DaX0Ozr28f4wdF2nt8nhuZJMXrxaGKmywydnKpqeC6Wq/Lh4RFK4QcfbqR/Leyjx9s\n+dCObTDRJQAAAHAoCIswCn9VzJgiUOm7hpYoCYKlk3INTaniOXK9eLLIXp82nMDmhzqZX3Ad3c/v\nLBIpQqZ4A0wb4wKpIdthy4Qd9leSDWnS3lNV5xOwOe7vjpQSAAAAB4awCKOIAw07vdOkvoYWrqzZ\nNTT7PJkXRGltXODih0V2sqjpBDYdhEVaJqkS1bCGpqNAIjem9iHRmKqMe8gHyGW6T+zvr9dkUcv1\nfeF+Jj60Y4OYLAIAAMChIizCKOIS5qRjsqh2GpoqpousY286aJom8tvve0ju/r7flYeu3Ai6kYLJ\noqizyOeHLUVnkRIlqhbcxKei5drUfi5/DU0vUTw9JOtIBkwWhZ1FQ9/V+bdK5xOwLENaBAAAgANF\nWIRRZNGJZcVkUfN962toYbB0MvUmi1Iljz5zJiIi7/vklSC88Vff8ug0NJ+/hlZ0FiXdk0Xl7XnD\nGppZeg1t+KdNJf27kfb9s6wN9vYxCMN5ZqcN+cMDAADAYSEswiji6Zc0UaL6rqGJNBZci1SF1SIi\nV27MgtdpOg1t2hQWeamO6yxSTZ1FxaX9YJjrljU0ux42qODaPr7/Y+yvZGhl0V5+sOUIc2wBxeoA\nAAA4VIRFGEWm65NFbZomixLVMlmUVH+iV67Po8mihrBoUn/d4DQ011lUnIbmhzdPPHsm77r/KRfO\naNMwWST+ZNESnUWD1tCK1+m3htZ8fV9UYdtW3wYODH9uAAAAOFSERRhFvIbW2lck1cSM/7V//5uO\nJ+76JK1uf/rGPFg9m3nXs441tLDg2jsNzYSrbL/49vvlm37+ncF940DIL7getIbm1ln6SwZMFvkT\nN/v4Abfqk9ru+8BhYbIIAAAAh4qwCKOoTxa1/2nVw6Kw3+imo2qyyF8ru3J9Fk4WZd1raC9+7gUR\nCTt/stzI1HYWSTi1c22Wy2mWB91F9c4iOZeTRfvO0B2DLeKvDgAAAIeGsAijyKNA49LJpOWeUusy\nSlR420VvssifOHri2fbOolwbSbwJpefffCz/6MtfISLhZE7uJouKNbR5NJ1UBET+yWLhx0RtjJss\nGhL8VIcqDXiQnSzqU3Bt2r7YD5xKhW2oitX5wwMAAMBhaf9EDwwQr6Hd3BUWRV/HHUb+ZJHfffT4\n1bNaWbU19045ExE5miRih4xyY+TbfundYkwxpXM8nVSTRV7gNC+fz58mqq2hiUhqC64H7EStMlmU\nDy643j9kRdgG99/tdt8GAAAAsHGERRiFDW4SVYQtN59MW+/b1Fnk8zuL/LWyx66eBgHRLPMni4ri\nahuwHE+S6tQybeRtH3pUREQ+58W3SpoU99M6nCyyQZQfAjWtodnppT5H2nuP9P53PzYnYw2tmuxg\nwgObRLE6AAAADhVraBiFDXzsSWZdk0XxJFG8lnbTsTdZlIZraH5A5K+hzXNThkDF10eT1IU6Ouos\nsn1KRuqrbCLhxFJ9Bcx4z9v6I9aYJT51VmHXgOcf9hI7gw/t2AbD/iMAAAAOFJNFGMXPf/MXyq+9\n5wH5k48+Lh955KoLi37yG14jL739puC+9TW08OuLR95paN43c23k0WdO3ddx0DNNExc8HXmTRf7q\nWq6NTBJVhFumXswtEk4WxeGENkUwlqhhUy7LfORUAwquw9PQ9vCDLetA2CJCSgAAABwaJoswilc8\n/5J8/1e/yn19S7mG9sbPeaG8+kW3BPeNJ4mUxJ1FflgU/ok+cPmGux6UU2vt1stERI7TxDviPrpf\nWhZcSxg4VfdpnywyxoiSco1t0Glo1Qlrfdlf05DX2VdV0fCW3wgOCp1FAAAAOFSERRjVjXkuIgsK\nrqNJotpkUcsamojIg09dd9dnZdDzvb/+fvnT//CETLw1tOlEuSLqPDoNzU4WFaeh1cMiv4sojyaP\njNjJIjVsDc1ddj/o409cky95yx/JY8+cup+lT8H13q+huQ/te/jD4dwipAQAAMChIizCqG7MeoRF\nEncWhd+/1FBwfddzLoiIyAOXq7Aoy7WcZbn8m3c/KA9duSGTVLnnOp6k1Wlo0alptttIm/opbvH9\n4w+JxhSTUUqt5zS0+x57Vh66ckMeuHzDTUn1W0Nrvr4vljlNDlgVf28AAAA4VIRFGJWbLDpuPw0t\nniSK19IuHnmTReWdn3/LsRxPEnngqXAN7cr1uXffqqfoKPVOQ4smhaZJ0W1kxDQGMXnHGpo2RpTI\n8mtoC+5nC7yNMYMKrvcdn9mxDUy0AQAA4FARFmFUp0utocVhkddZVK6hHU8SeeGtJ8Fk0SzX8tS1\nWXXfRLkPd0eTpPk0NG0kSYrZJmNEZln3h8CmQEgpkTRZcg1twWPsWpxddyvec4/JItM+DbUPqs6n\nPfzhcG5xCh8AAAAOFWERRmVLp28+aZ8sqhdch1Jv9MgWXB9NUnnhrReCSaJ5puWyFxaliXKTOe2n\noeliWkkVHwQXBTFxIGRM8X6VGlg83XNCwb5/rc2ggutwDW3/PtlygDm2ib87AAAAHJr28Q9gBYMm\nizoiSztZdJQmcvulo+B781zLZS88mqaJnOVeWNQwWZTrorNIlWlRU2eRL55kMVKshyVKDZo2MLUr\nzWxptzbVxNWi93gI6CzCNjDRBgAAgEPFZBHW4pauyaJoliheQ/NN3WSRkjtvOXG3X5imMs+NPHW9\nZbIoTRpPQ7MhjFJF8BOfdhaLv621PQ1t2GSRXqWzqM9k0b43XJc/1KBpLmBF/LUBAADgUBEWYS0u\nDZgs6pJ6k0X+atuFo1TmuZYr3hraNFVylhWdSceTxE0s2QBGpJgsmqTeaWgLw6L6ZJGSYrJoUdAU\nPM5NxixYQ2voLMr7FFybxqt7oyoaBjaIiTYAAAAcKMIirEUaH3nmib/VPVlUhkWTJAigiskiXZss\nmpeF1UeTarLIBkgiInk5saNEiTFm4aSKjgIhY0REiSSDC67tOkv3/ea2s8ibLOpVcO3FKPu4MkPR\nMLbB/XdLTAkAAIADQ1iEUf2DL3mpPPdi+wqayLA1tElq19ASufm4CouOp4nMcxMUXk+SRGZ5EQwd\npVVn0ek8nCxKEynX0GThdFAcThgpwq5EDQtl+k7G+J1F9rfC6pX/78DvAptDVxYAAAAOFWERRvVP\nv+bV8t5/+rc77xNPFvlZ0dEk/JO0BdfTNJGbjhsmi7w1tEnafBra6dybLNJGUlXEVcYsDmJqa2im\nWkMbEuL0nYypwiIzqODaf959/GDbdzILGBMTbQAAADhUnIaGzVPxZFFx+c4f+Ao5TtPgexN/Dc0L\niy4epfLktZlc8dbQJomSz7zzFhERedULb3GrcKfeGpqISJokkpef/oYWXBtjC66HraG57pMFkzGu\nX8lUv6ZeBdct1/cFEx7YBv7eAAAAcKgIi7BxNipSyoYvxS3Pv/mkdt9J2VJ9nIZh0UlDZ9EkSeTv\nvuYu+dyXPEde8fxLcu+DT4tIuIYmIpImIqa8adHUTh5PFpXvW6l6n1GXvpMxs4bOol4F13vOTXjs\nZRSG86rqLAIAAAAOC2ERNs6GIIlSkhsj7Y1FxQlnIs0F11lu5Mw76SxNlSil5BXPv1Q8f7nR5q+h\nFbcrUTYsWthZNNIaWs+7zr3OIvv+8z4F194L7OM0hP359vFnw/nV9xRDAAAAYN/QWYSNs+tVibtc\nXHBddBZVK2oXjorJopkXFsX/7//EnYYWTRYp5R1L3x3E1NbQyvefDj4Nrbxc8KHTnyyyReCLVuX8\n5y+u7+8H2/39yXAemegSAAAAOBSERdg4Gw25CaOOv0K/s+jm4+qUtQvTVGZZERbZ6aN5Hq+b2bAo\n7iyqzmNbNFkUTw/pcm1OqWGnlLnJmAX3swXXxlRh2qL3eAjoLMJW9D3GEAAAANgzhEXYOHukvQ2L\nVMcimh8WnUyrP9eTaSqzXMss13LLSREixaGKmyyqdRb5k0WL1tCiaaBybS5RalBw0fs0tMyuWxnX\n5dSr4PpQTkPjUzu2gL87AAAAHBrCImyNnZzp2EJza2hHaeLCE5EiLLLF1bdeKMKitsmiuLOoCIvs\nNFLxIdCGUk2CIEbsaWjdIc7TN+by2T/4NvnLv3kyeI6Fp6H5nUUu0Op8SK/n3XXuV73fPybOmb4h\nLwAAALBvCIuwcSrqKlIdaZFfcO079r6+uQyL4pPNUtUVFkn5mCKJmaTt70FH5dGJKgquu6aSnro2\nk6unmTzw1PXW+zSZN56GxnFobANhG/i7AwAAwKEiLMLGVV1Fdh2t/b6TpJos8vnh0S3lKWlZFKrY\nLqTGguty9c2urk3T9v8U/ExIe2toXRtsNkiaaz3opDLXWSTihUXdj3EPcK+xfx9t7U80pCcKWBWn\n8AEAAOBQERZh42w2lEbdRU0mLZNFU28S6Ba3htbcWRRPFiUNnUXdYVEY9ihVBFFdoYx9TK5NbY3N\n+uOPPib3fPJy8Dh7Gpr/3H0mi0zL9X3Bh3ZsQ7X9yB8eAAAADgthETbOTRbZzqKO+7rJolpYVH1t\nO4viyaKqs6hpskjKxwzvLBJR5WRR+wdIN1mUhx8z/Yf8yO9/RH72Tz4WPG6eV2to9pE5CQlHmGMr\nOIUPAAAAh4qwCBtnp3pUj84iO1kUT/74X9vT0OZZy2RRFk4WTdJ6Z1H/ySIjiSrec581tDxaQ/Pj\njlmuaye42ckirav1t14F13t+Gpq4D+37+MPhvOKvDQAAAIeKsAhbY4d5ujqLbJH1yTQNbvfX0G46\nKr7Xd7LIFlQXjzFuraxN4xragtPQ7Pcy3T5ZpLWphR+2X8lIFYz0W0Mzjdf3hf2Z9u8nw3nm1h+3\n/D4AAACATZts+w3g8FRraIsni17/8tvkh970WfLZd90qIiK/99++QT72xLNuAkdE5OKxLbhuPg3t\nLKufhmZlWkuqlLtvEz+rMWJEDVhDy3LTOvWTaVN7Dn8NbchkkW8fh2/cz7SHPxt2wD7+RwUAAAB0\nYLIIG6fcRNHi09COJ6l84+vvdgHPq190i/xnn/OiYG3s0nExWRT3Dil7GlrDZJFyJ40ZSRPVWbLd\nNFmUKiVdAz8uLNKmdeon10aiTu7qNDRjhk0W7flnWYqGsQ2us2i7bwMAAADYOCaLsHE2lrGrX12T\nRW38sOju226Sf/yVnyFv+rwXBfdpmyyaJF7BdV6ERV1vIQiLxIZN3Wto1WSRbp0syhvW0Oa2s8hU\nH1D7FFzv/2lo4SWwCW79kb87AAAAHBjCImxcksRraMOf42iivOuJfPdXvrJ2n9bT0LxwKNNGUrVo\nssi/bkRU8d7zjobr3E0Fhffxv8ob1tCqyaIqjGINjQ/t2C6K1QEAAHBoWEPDxrnJoqi7aAh/sqjt\nJDN3Gto8nCxKkrDgOlmwhhZ8UCyyIkmS7okfuzmW6fbOotyYIEzS2si83EvTpnpcvzW0/f4wW60D\n7ffPifOFNTQAAAAcKsIibJyKJoq6OovaTLzjy+yJaTE7WRQXX0+8yaJc6x5raNV1I8X7X1hwbU9D\ny3V7Z1Fugueee6GQGVhwHb6V/fto6zqL9u9HwznG3x0AAAAOFWERNs4GM7ZTqGoQ6i9eQ2vSFkIl\nqnrFeW4kWbiG5hdcG0nKNbSOLTTRfsF1S6FQFnUW+Se8aSODCq59e/nBliPMsQVMFgEAAOBQERZh\n42xUs0pnkb961hYWKdU8MZQmyr1oro1MEiVJx38Jflik7Rqa6l79sutluTat5dO5CSeL/LDI+Gto\nfFJlwgNbUXVl8YcHAACAw0JYhI2zEz/VGtpqnUVHLZ1FItX0UnBbUvUmZbo4Da3rPfxPv/1Befvf\nPCEixYfHPmtodvVtnofTQ/71XIedRfM8DKXs8+uuESb3vM3X90X1O9jDHw7n1j7+twQAAAD0QViE\njXNraMk4k0XTlskikerkNV+aJFXBda4lSaoepSZ//NHH5c/+ugyLyskipZR0bYdpb4WsabLIlOXW\n7Wto1URS1qfguqUXaV/Yn6hHbjaaBy9fl995/8Obe0EAAAAAOCcIi7Bxdg3NhkXLTBYdrTJZ5K2n\nZdpIqtTCkm072WKMLbiW7oJrO1nUchqaji5FRGa5Du5XBU7d7+0QuO6YDY56/Nq7H5Tv+dX3buz1\ncP7YvzcmjAAAAHBoCIuwccqtoa0wWeQXXHeFRQ0pUOKtoeXaSLJgDc3eT6T48KhU8bxdYZELenIT\nbE7F00L+GlrQWSTV4/oUXO/7Gto2ltBybYKicRyequCavwEAAAAcFsIibJwNiRLXWTT8OSZlI/U0\nVY2rZtVr1W9LE2+yKNf9Jou8U5GKguvu09By/zQ0f0XMTQuVfUT+GloenobmAqcen1PbSrT3xTYm\nPFxn1D7+QtELxeoAAAA4VIRF2LiX3n5R7rj5WG676UhEuvuC2thpomnHVJFI82TRJFFuFc4WXC96\nD9oLK1R5mFqfNbRM63DqJ/q+/715HnYWuVU10gpnk7+JalWQ3/+hMl5IDAAAABwSwiJs3Gs//Xny\nrh/4SrnlZCoi1UrYEHYN7aij3FqkubMoUcq9aJbb09C6X8+FO2IkKU9D68oQtDdBFNzNrZY1TBZl\nYWeRfaRfcP3QlRvyzOm89nrhiWvdP8tQn3zyunznr9wjp/N83CceYBudRcbU/41wWOx/g/wJAAAA\n4NAQFmF73Bra8LjIThR19RWJVKeh+fdLvY6iTOvg6zb+SpJSxepc3jHxk9mC61wHYUMVANkVs+Y1\nNGOMO23Nryz6xp97h/zEH/517fXCNbRxP9m+6/6n5Hfv/ZQ8fOXGqM87xDY6Y/QWVt9wPtFZBAAA\ngENDWIStsatgy4RFk2TYZNGFo7S6LVFhwbXqHxYVF6rsLOoouNbeZFHTaWgNa2j+ZJGfQ/mTRZev\nz+TpG/XJosDIn2v1OZiwqSaLNvearKFhG393AAAAwHlAWIStqU5FW+axSo7SZPFkUfncF+OwyK6h\nuc6i7terpoiK09CSpHsNrb3gunpdkfY1tKKzqF5wnWnjHutb54fZaqVufa+xSPXb39yndgquwT89\nAAAADhVhEbbG5jPLhEUixUloiyaL7BrahakXFin/NDRTnoa2aLKouDSmCKCSRQXXNhTKTfCJ04Yd\nuQ4vRcKCa+OfhuZNFmW5aSm8Ng3XxmHfVtfa3bptY8LDTYExVnK4+LcHAADAgSIswtaoFTqLREQm\nabJ4DS2pr6ElDaehLSq41t4kkBqwhpZFBdf2IU2noYUF18a7b3WfTOvGySLf2CXQ+XlYQ9tC0bBb\nPdziRBW2y020ERoBAADgwBAWYWtsYLP8ZNHiNTTXWeRNFk2CNbR+Bdc2MDHl+1VKda4n2ftnuQ47\ni8S+bsMaWh52FrnOHO+FMm0aQ5u1rqE1vNdNq44w38YaGkHBoaKzCAAAAIeKsAhbk5R/fctOFh2l\nyp2K1v4aLZNF5WvmuQm+buOvoSkp19A60iJ/zayps6hpDS3uLBJ3cpqunss0r4OZluuw3QZ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Hr3A69tcZNFrKEBAADgwBAW4SAl3l/+7ZeqLiM/IGoLMpSE33BraFrksauncn2WFZNFiQRhUZIo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\nSOHkci9Om5pzH1ksAr5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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7834db7240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(loss_history)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
